Hindu Research Articles

Deep Neural Networks for Location Reference Identification From Bilingual Disaster-Related Tweets

Twitter is increasingly being used during disasters to communicate with authorities, ascertain the ground reality, and coordinate real-time rescue and recovery activities. Geographical location information about users and events is critical in these scenarios. Geotagged tweets are extremely infrequent, and other location fields, such as user location and place name, are unreliable. The extraction of geographical information from tweet text is limited by the fact that individuals frequently publish multilingual tweets that contain numerous grammatical and spelling errors, as well as nonstandard acronyms. As a result, determining the geographical location of the tweet is a challenging problem. This article presents a technique based on deep neural networks for extracting geographical references mentioned in bilingual tweets. Several deep learning-based models, including convolutional neural networks (CNNs), long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), and attention-based Bi-LSTM, are implemented on real-world English and Hindi language tweets to determine their suitability for extracting location references. The proposed CNN, along with a conditional random field at the last layer, is found to perform better than other models, with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F_1$</tex-math> </inline-formula> -score of 0.858. The findings of this study can aid in early event detection, pinpointing the area of devastation and victims, real-time traffic management, and a number of other location-based applications. The suggested system’s code and trained model may be obtained at https://github.com/Abhinavkmr/Bi-lingual-location-reference-identification.git.

Ramottaratapinyupanishat and its Invaluable Contribution of ‘Rama Taraka Mantra’ to Human Society

Purpose: This article reveals about “Ramottaratapinyupanishat”, which is a part of Atharva Veda. This Upanishad has contributed the invaluable “Rama-Taraka-Mantra” for the wellbeing of human society. In Sanatana Dharma, the ultimate abode of every human being is Moksha and this Mantra is the Key to open the door of Moksha. Methodology/Approach: Here, Rishis like Bruhaspathi, Bharadwaja and Atri who are the disciples always engaged in austerity for the prosperity of the whole Manu Kula, approach Yajnavalkya and pray him to explain about the ways and means to get relief from this non-stop wheel of Samsara chakra and to attain Mukti or Moksha. This paper is the outcome of practical approach after theoretical explanation. Findings: To their queries, Yajnavalkya unfolds the whole Upanishad by decoding the great ‘Rama Shadakshara Mantra’, its unique strengths, secret values of each and every syllable, methodologies to be followed during the Sadhana and its glorious outcomes. Originality/Value: The contents of this paper are the final prosedings of Upanishat Havana’s Vakyartha gosti conducted after the Havana on 1-11-2019. The value of the contents is highly merited and is evergreen. Paper Type: Practical research.

Impact of Socio- Economic Status on the Educational Achievement of Secondary School Students in Vadodara

With the onset of COVID-19 pandemic, most of the students and their families were affected by economic burden and became unemployed. Those who had business also suffered, unemployment in India effected the future of the students and their parents. Paying fees in schools became a problem for parents. Many students lost their father or mother. Research has shown that the effect of socio-economic status on the academic achievement of students was observed due to corona. Many parents are not educated. If the size of the family is large, then out of 4 children, one or two children are not able to get admission in the school. The present study will help us to know the importance of the situation of our country along with the academic achievement of students. The objective of this present study is to know the socio-economic status of secondary school students of Vadodara district and the problems faced by them in their academic achievement. There are many factors affecting academic achievement. psychological, social, economic and environmental etc. The objectives of the study were to identify the level educational achievement of secondary school students of Vadodara City and to examine the influence of socio-economic status on the educational achievement of secondary school students The descriptive survey method was used for the present study. 50-students and parents of the two Hindi medium schools namely Shri Krishna Hindi Vidyalaya and Adarsh Hindi Vidyalaya were selected as the sample for the present study. It has been found in the present study that the academic achievement of low-level students, average level students, high level students were investigated the level of all the students, mean scores of high-level students were 212 and the marks of average level students were 142 and the lowest low level of students is 57. To see the impact of socio-economic status on educational achievement, t-test was conducted, it was found that statistically there exists no significant difference in socioeconomic status and educational academic achievement It becomes important to be conclude that even the status of social or economic level is low but efforts can be made to attain expected educational achievement and lead to a totally developed personality for which education is aimed for.

Acculturation of Hindu and Buddhist Culture at Goa Giri Putri Temple Nusa Penida

The purpose of this study is to determine the process of Hindu-Buddhist cultural acculturation in Goa Giri Putri Temple, identifying the form and meaning contained in the cultural acculturation. This study uses the theory of cultural acculturation to analyse the process and forms of the cultural acculturation that occur in the temple and multiculturalism theory to analyse the meaning/values involved in the cultural acculturation. The method used in this research is qualitative. Data were collected through an in-depth interview and observation. The data were analysed using a descriptive-analytical technique. The findings show that the process of cultural acculturation in Goa Giri Putri temple is the openness of the community to the entry of outside culture (Chinese culture) into Hindu culture and the existence of community beliefs or faith. Acculturation can be seen in the form of Buddhist worship statues placed alongside the worship (pelinggih) of Hindu gods at the Goa Giri Putri Temple. The means of worship used also do not distinguish between Hindu and Buddhist beliefs. Hindu-Buddhist cultural acculturation in Goa Giri Putri Temple has the meaning of providing an understanding of multicultural values and socio-religious values for the people of Karangsari Hamlet, Suana Village, Nusa Penida.

English Language Supremacy in India: Where Literacy Rate is Check by If Person can Read or Right in Any Language

IN INDIA where different type of languages exist how any specific language can be supreme? Here literacy rate is check by if the person can read and write in any language no language is barrier to check literacy rate the why any specific language is barrier or even people judge the status and treat other person by the mode of communication {English}. Only 10% people in India who knows English. Around 20-30% of people don't know Hindi in India. The constitution of India states under Article 348(1)(a) that all proceedings in the Supreme Court and in every High Court, shall be in English language or Hindi language. Use of any language according to the place and tounge of the people living there or the language which is easy to understand by the people living there is still better that to use any specific language like English or Hindi. The people for whom the courts came in the existence or who file cases in courts for justice if they are not able to understand that what the judge and advocate is arguing or talking about then how they can understand immediately what is going on in their own case. Along with this so many advocates who have efficient knowledge but just because of the language barrier they can't be part of higher courts.

Translation and pilot validation of Hindi, Marathi, and Bangla translation of quality of life EORTC module (QLQ-SH-22) for assessing sexual health-related quality of life.

To translate and validate the European Organization for Research and Treatment for Cancer (EORTC) module for assessing the sexual health-related quality of life in cancer patients (QLQ-SH22), in Hindi, Marathi, and Bangla languages for clinical use. The EORTC QLQ-SH-22 was translated into Hindi, Marathi, and Bangla by adopting standard guidelines given by EORTC. Initially, the original questionnaire was forward translated by two separate translators, followed by the reconciliation of the forward translations by a third person. This was followed by two back translations of the reconciled version into English by two other translators. These back-translated questions were then compared with the original EORTC questions for accuracy, and once acceptable, a preliminary questionnaire was prepared in all three languages. These questionnaires were then pilot tested with 30 patients (10 for each language) diagnosed with any of the cancers in the pelvic region who are expected to be at risk of sexual quality of life due to tumor or treatment like pelvic radiotherapy. Participated patients had never seen or filled the questionnaire before, each patient was interviewed after filling the questionnaire for difficulty in answering, confusion, difficulty understanding, or if any of the questions were upsetting and if patients would have asked the question differently. None of the patients reported any changes or suggestions for all the three translations. All the translated questionnaires were well understood by all the patients. Pilot testing reports were sent to EORTC. After reviewing the entire report of Hindi, Marathi, and Bangla translations, these questionnaires were approved by the EORTC translation unit. The questionnaires are reliable with Cronbach's α for Hindi, Marathi, and Bangla being 0.69, 0.66, and 0.86, respectively. The final Hindi, Marathi, and Bangla translations of SH 22 have been approved by the EORTC and can be used to assess the sexual health of cancer patients in routine oncology practices and/or clinical studies.

Ensemble Classifier for Hindi Hostile Content Detection

Detection of hostile content from social media posts (Facebook, Twitter, etc.) is a demanding task in the field of Natural Language Processing. The increase of hostile content in different electronic media has opened up new challenges in language understanding. It becomes more difficult in regional languages. AI-based solutions are required to identify hostile content on a large scale. Although a satisfactory amount of research has been carried out in the English language, finding hostile content in regional languages is still under development due to the unavailability of suitable datasets and tools. In terms of the number of speakers, Hindi ranks third in the world and first on the Indian subcontinent. The objective of this article is to design a hostile content detection system in Hindi using coarse-grained (binary) classification and fine-grained (multi-class, multi-label) classification. We note that different baseline learning methods with different pre-trained language models perform differently. Using the Constraint 2021 Hindi Dataset, this research proposes a Bidirectional Encoder Representations from Transformers–(BERT) based contextual embedding technique with a concatenation of emoji2vec embeddings to classify social media posts in Hindi Devanagari script as hostile or non-hostile. Additionally, for the fine-grained tasks where hostile posts are sub-categorized as defamation, fake, hate, and offensive, we develop an ensemble classifier varying different learning methods and embedding models. With an F1-Score of 0.9721, it is found that our proposed Indic-BERT+emoji model outperforms the baseline model and other existing models for the coarse-grained task. We have also observed that our proposed ensemble method provides better results than the existing models and the baseline model for the fine-grained tasks with F1-Scores of 0.43, 0.82, 0.58, and 0.62 for the defamation, fake, hate, and offensive classes, respectively. The code and the data are available at https://github.com/skarifahmed/hostile .

End-to-end Multi-modal Low-resourced Speech Keywords Recognition Using Sequential Conv2D Nets

Advanced Neural Networks are widely used to recognize multi-modal conversational speech with significant improvements in accuracy automatically. Significantly, Convolutional Neural sheets have retreated cutting-edge performance in Automatic Voice Recognition (AVR) recently more appropriately in English; however, the Hindi language has not been explored and examined well on AVR systems. The work in this article has exposed a three-layered two-dimensional Sequential Convolutional neural architecture. The Sequential Conv2D is an end-to-end system that can instantaneously exploit speech signal spectral and temporal structures. The network has been trained and tested on different cepstral features such as Frequency and Time variant-Mel-Filters, Gamma-tone Filter Cepstral Quantities, Bark-Filter band Coefficients, and Spectrogram features of speech structures. The experiment was performed on two low-resourced speech command datasets; Hindi with 27,145 Speech Keywords developed by TIFR and 23,664 (1-s utterances) of English speech commands by Google TensorFlow and AIY English Speech Commands. The experimental outcome showed that the model achieves significant performance of Convolutional layers trained on spectrograms with 91.60% accuracy, compared to that achieved in other cepstral feature labels for English speech. However, the model achieved an accuracy of 69.65% for Hindi audio words in which bark-frequency cepstral coefficients features outperformed spectrogram features.

A textual question answering and handwritten answer evaluation system for hindi language

Textual Question Answering targets answering questions defined in natural language. Question Answering Systems offer an automated approach to procuring answers to queries expressed in natural language. The need for Multilingual Question Answering without performing machine translation is ever existing. Besides that, automating tasks with the help of technology to assist humans, has been the main aim of research in recent years. This paper presents an automated answer evaluation system for reading comprehension-based questions in the Hindi language without requiring translation in any other language. The system accepts text, question, and handwritten answer of a student in the form of an image for answer evaluation. This is accomplished by developing a textual question-answering system for reading comprehension. It is an extractive approach that utilizes RoBERTa transformer model and fine-tunes it for Hindi question-answering. The answer to the question is extracted as a span from the provided text. Further, a handwritten text recognizer model is developed employing a Convolutional Recurrent Neural Network with Connectionist Temporal Classification module along with two layers of Bidirectional LSTM. Experimentation is performed using existing as well as self-created datasets to show the effectiveness of the proposed approach. An accuracy of 98.69% is obtained on the self-created Hindi-QA dataset and the proposed system outperformed the other existing methods. The paper also discusses potential research directions in the field.

A Legal Analysis of Cyber-Enabled Wildlife Offences in India: A Qualitative Case Study of Sea Fans (Gorgonia spp.) on YouTube

With the advent of the Internet, offences against threatened species have transitioned online. Such species are directly or indirectly traded on social media despite being protected under Indian wildlife law. A qualitative case study was undertaken to assess the preparedness of national law and policy in prohibiting such offences. Sixty-three YouTube links on sea fans in the Hindi language were accessed over 8 weeks, and the information generated by both content creators and audiences was gathered and categorized for analysis. The legal provisions were then interpreted and applied to assess the extent to which the parties involved could be held liable. Our investigation shows that of these video links, the content creators directly offered specimens for sale in 15.87% of instances, demonstrated physical possession of wild specimens in 23.81% of these posts, and were involved in both activities in 20.63% of the links, which in our analysis is explicitly prohibited under national law. The remaining 39.68% of video links merely disseminated information on the relevance or usage of species in occult or religious practices, for which no express legal provision currently exists. Certain indirect legal provisions were found to be relevant; however, there were challenges associated with their implementation. Even the liability of a social media company was found to be limited if it can be demonstrated that the company exercised due diligence. Therefore, there is a need to explicitly regulate online content that has the potential to drive an unlawful demand for protected species alongside the imposition of enhanced liability on social media companies. Such measures, coupled with community awareness, can reduce cyber-enabled wildlife offences committed through social media channels.

Spider Monkey Optimization with Deep Learning-based Hindi Short Text Sentiment Analysis

Sentiment analysis (SA) intends to categorize a text respective to sentimental polarity of individual opinions, like neutral, positive, or negative. The study of Hindi is limited because of the grammatical and morphological complexities of the Hindi language while many research work concentrates on drawing features from English text. The hindi languages make the sentiment classification procedure for Hindi short text a tedious process. The Hindi language has complicated morphology and variation based on phonetics, spelling, and vocabulary; the common usage of numerous dialects between Hindi in India produces a massive volume of glossaries. In this study, we introduce a Spider Monkey Optimization with stacked recurrent neural network (SMO-SRNN) for short text SA on Hindi Corpus. The proposed SMO-SRNN technique mainly aims to identify and categorize the Hindi short text into three distinct classes, namely negative, positive, and neutral. In the presented SMO-SRNN method, the SRNN approach is exploited for the investigation and classification of sentiment. Moreover, the SMO model is employed to finetune the hyperparameter related to the SRNN model. A detailed set of experiments is applied to ensure the high efficiency of the SMO-SRNN algorithm. The comparative outcome highlighted the enhancement of the SMO-SRNN technique over other methods.

Comparative Assessment of Online Written Health Information on Treatment of Erectile Dysfunction in English and Hindi Language Webpages

Objectives: To assess and compare the overall quality of online written information on the treatment of erectile dysfunction (ED) in English and Hindi language webpages. Also, correlates of the quality of online health information were explored. Methods: First 50 links obtained on Google search in both English and Hindi language were screened, and a total of 86 (45 English, 41 Hindi) webpages providing patient-oriented information on the treatment of ED were analysed. Content quality and reliability were assessed using the DISCERN scale and the JAMA benchmark criteria respectively. Additionally, aesthetics, interactivity, and readability were evaluated. Results: The DISCERN score indicative of content quality was significantly higher for English webpages compared to Hindi webpages. English webpages were more likely to meet disclosure and attribution JAMA criteria for the reliability of medical information. English webpages with HONcode certification were more likely to have better content quality than those without it. However, none of the Hindi web pages analyzed were HONcode certified. Conclusion: English language webpages provided better overall quality of information on treatment of ED as compared to Hindi language. HONcode label might be used as a proxy indicator of better content quality for online resources informing on ED treatment by laypersons. There is a need to develop and popularize the usage of HONcode or other similar online health information quality accreditation systems for webpages in non-English languages like Hindi.

Translation and validation of the Hindi, Marathi, and Bangla versions of the European Organization for Research and Treatment of Cancer Quality-of-Life Questionnaire: Anal Cancer (QLQ-ANL27) module: A prospective cohort study

Background: The European Organization for the Research and Treatment of Cancer (EORTC) has developed a commonly used validated questionnaire specific to anal cancer (EORTC QLQ-ANL27). It is used as an adjunct to the core EORTC quality-of-life (QoL) questionnaire QLQ-C30. This validated questionnaire was not available in any Indian language, and therefore, Indian patients not familiar with English could not fill it. Objective: We aimed to translate and validate the EORTC QLQ-ANL27 module in Hindi, Marathi, and Bangla languages. Materials and Methods: This study was conducted in the Department of Radiation Oncology at the Tata Memorial Hospital, a tertiary cancer center in Mumbai, India, from September 01, 2022, to March 31, 2023. The QLQ-ANL27 questionnaire was translated into Hindi, Marathi, and Bangla languages using the standard EORTC guidelines. The overall process comprised two independent forward translations of the original English questionnaire into the target languages, followed by reconciliation between the two forward translations. The reconciled version was then back translated to English. The report generated was sent to the EORTC translation unit (TU) for review. Once approved by the EORTC TU, these translated versions were pilot tested on 30 patients (10 for each language) with cancer of the rectum or anal canal. After responding to the questionnaires, each patient was individually interviewed to explore any difficulty encountered while answering the QoL questionnaire. The interviewer specifically asked whether the patients found any words or sentences difficult to answer, confusing, or upsetting, and for suggestions on better phrasing. Results: The EORTC QLQ-ANL27 was translated to Hindi, Marathi, and Bangla, followed by back translation into English within a period of 2 months between September 2022 and October 2022. The translated versions were approved by the EORTC TU in October 2022. Validation of the translated versions was conducted between December 2022 and March 2023 in 30 patients diagnosed with anorectal cancer. The median age of the patients was 55 (interquartile range, 29–77); the male-to-female ratio was 2:1. There were no suggestions or doubts in the Hindi, Marathi, and Bangla questionnaires during the pilot testing. After reviewing the pilot testing reports, the EORTC TU approved the translated versions of QLQ-ANL27. The reliability of the translated questionnaires was confirmed using Cronbach’s alpha, which were 0.838, 0.743, and 0.808 for the Hindi, Marathi, and Bangla versions, respectively. Conclusions: The Hindi, Marathi, and Bangla translations of the QLQ-ANL27 module have been validated and approved by the EORTC and are now available for use (Clinical Trials Registry-India, CTRI/2022/12/047970).

Akuntabilitas Auditor dalam Perspektif Ajaran Karmaphala

The significance of an auditor's accountability is widely recognized in the execution of their professional duties. Numerous auditors encounter significant challenges stemming from the disregard of ethical principles, instances of error, and breaches of professional norms and codes of ethics. The concept of karmaphala, or cause and effect, is recognized in the Hindu religion. This study investigates the concept of auditor accountability via the lens of karmaphala teachings, building upon the aforementioned context. This study employs a qualitative methodology, specifically utilizing a library research strategy. The findings of the study indicate that auditors exhibit heightened diligence in their evaluation of facts, assumptions, and ethical boundaries while applying the karmaphala philosophy. This approach aims to prevent unethical conduct that may have adverse consequences for several stakeholders.

An empirical comparison of Hindi-BERT and MuRIL for hate speech detection on social media platforms in Hindi language

An empirical comparison of Hindi-BERT and MuRIL for hate speech detection on social media platforms in Hindi language

Sentiment Analysis of Custom Speech Corpus: A proof of concept for NLP

This paper presents an innovative, custom Hindi Speech Corpus dedicated to assessing the positive intensity in Hindi language. By meticulously gathering voice samples from individuals across diverse demographics, this corpus is well crafted for acoustic research in Sentiment Analysis. Several sentences spanning a spectrum of sentiments (extremely positive, positive, neutral, negative) were acquired from participants. The resulting corpus comprises of 225 audio files. To guarantee the consistency and to accommodate domain knowledge based nuances, the sentiments and its intensity (high, medium, low) were classified by Expert annotation. We used PowerBI for attaining insights into emotional landscape of the corpus. Employing exploratory analysis and Sentiment Analysis, the corpus is analyzed to unveil linguistic features indicative of positive intensity in Hindi speech. This study advances the understanding of positivity expression in Hindi and furnishes valuable resources for linguistic investigations in the scope of Hindi language. It is observed that positive sentiment has the highest count at 58 and the lowest count is for very negative at 27. The main contribution of current work lies in creating the custom dataset in Hindi which to our knowledge is first of its kind. Also, we did not come across any dataset focused on intensity of positivity. These contributions shall definitely be beneficial to future researchers in exploring positive affect related research.

Comparing Carefully

Abstract A contribution to the Common Knowledge symposium “Caroline Walker Bynum across the Disciplines,” this essay explores the side of Bynum's scholarly personality that may be regarded as comparativist. She is interested in comparison with regard to periods of time, with regard to ritual and gender-based religious practices in the Christian West, and with respect to similarities that might be claimed between elements of Christian and non-Christian cultures. Her thoughts about morphology, materiality, and gender extend beyond medieval Europe to the world at large. Her coedited volume Gender and Religion (1986), the first of its kind, has figured importantly in the development of the field many call comparative religion. Here Bynum's impact on selected scholars of Buddhist, Hindu, Muslim, and Sikh religion — as well as of non-Western Christianity — is assessed. This essay concludes with the text of a response delivered by the author, who is a scholar of Hinduism, to Bynum's Lionel Trilling Lecture at Columbia University, “Am I My Body? Medieval Theories of Bodily Resurrection and Some Modern Implications” (1991).

Comparative Evaluation of Depression, Anxiety and Quality of Life between Clinical and other than Clinical Branch Postgraduate Medical Students: A Cross-sectional Study

Introduction: Medical training has been reported to be stressful. Clinical branch residents were found to be more anxious when compared to other than clinical branch residents. Heavy workloads and long working hours usually contribute to stress, resulting in fatigue, depression, and anxiety. Aim: To compare depression, anxiety, and Quality of Life (QoL) between clinical and other than clinical branch postgraduate medical students. Materials and Methods: The present cross-sectional study was conducted in the Department of Psychiatry at the Institute of Medical Sciences (IMS), Banaras Hindu University (BHU), in Varanasi, Uttar Pradesh, India. The data were collected from 150 residents through face-to-face interviews and by applying the Hamilton Anxiety Rating Scale (HAM-A), Hamilton Depression Rating Scale (HDRS), and World Health Organisation Quality of Life Brief Version (WHOQOL-BREF). The data were analysed using International Business Machines (IBM) Statistical Package for the Social Sciences (SPSS) Statistics 23.0 software. Results: The present study found that the majority of residents were male 108 (72%), belonged to the Hindu religion (134, 89.33%), were unmarried (150, 83.33%), and resided in the hostel (118, 78.67%) during their residency tenure. The prevalence of depression among clinical branch residents was 52 (50.0%), and in other than clinical branch residents, it was 17 (36.96%) (p=0.633). The prevalence of anxiety among clinical branch residents was 65 (62.5%), and in other than clinical branch residents, it was 18 (39.14%) (p=0.002). QoL was better in other than clinical branch residents compared to clinical branch residents in physical health, social, and environmental domains (p&lt;0.04). Conclusion: The study concluded that clinical branch residents were experiencing significantly higher levels of anxiety. Overall, the QoL of residents in other than clinical branches was better than their counterparts in clinical branches.

Hooray for Bollywood: using Hindi language films to teach economics

Hooray for Bollywood: using Hindi language films to teach economics

Hooray for Bollywood: Using Hindi Language Films to Teach Economics

Hooray for Bollywood: Using Hindi Language Films to Teach Economics