1,722,928 research outputs found
Atypical Attitudes: How India Coped With COVID-19
No full textA reflection provided by Bhavya Shah of Stanford University
Oral History Interview with Bhavya George
No full textBhavya George is the Climate Change Program Coordinator for the Keystone Foundation, located in Kerala, India. The narrator discusses her work with barefoot ecologists and her efforts to connect with and support women, Indigenous people, and local communities.https://commons.library.stonybrook.edu/project-india-keystone-foundation-barefoot-ecology/1000/thumbnail.jp
Open Educational Resources (OER) analysis of NARS Institutions in India
No full textOER in ICAR and Agricultural universities in India. The study conducted in 2014
Open Educational Resources (OER) analysis of NARS Institutions in India
No full textOER in ICAR and Agricultural universities in India. The study conducted in 2014
Explanation mining
No full textIn this thesis, we propose the idea of computational analysis of explanations. Explanations are used to provide an understanding of a concept, procedure or reasoning to others. Although explanations are present online ubiquitously within textbooks, videos, blogposts, discussion forums, and many more, there is no way to mine them automatically. As a result, users in need of an explanation have to rely on search engines and potentially read through multiple documents in an attempt to find a suitable explanation. This process can be highly tedious for them and may not even be successful in some cases. On the other hand, there are many users such as educators, authors, who write explanations and can benefit from assistants that help enhance the quality of their explanations. The goal of computational analysis of explanations is to assist both these kinds of users. In this work, our focus is on Explanation Mining to assist users seeking explanations.
For understanding some of the linguistic features of explanations across multiple domains, we first apply standard Learning-to-rank models to rank explanations collected from the Explain Like I'm Five (ELI5) reddit forum. Based on cross-domain experiments, we find that a model trained on a sufficiently large dataset achieves decent performance across all domains which suggests that there are some common markers of explanations. Next, to apply this knowledge to the practical problem of mining explanations of educational concepts, we propose a baseline approach based on the popular Language Modeling approach of information retrieval. We show that incorporating knowledge from a model trained on the ELI5 dataset in the form of a document prior helps increase the performance of a standard retrieval model. This is encouraging because our method requires minimal in-domain supervision, as a result it can be deployed for multiple online courses. Finally, we show a demo system that acts as an assistant to online learners while viewing slides. The system enables users to select any piece of text on the slide and find an explanation for it. We conclude with some interesting directions for future work in this field.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01The student, Bhavya, accepted the attached license on 2020-05-12 at 14:25.The student, Bhavya, submitted this Thesis for approval on 2020-05-12 at 14:30.This Thesis was approved for publication on 2020-05-13 at 08:19.DSpace SAF Submission Ingestion Package generated from Vireo submission #15341 on 2020-08-25 at 17:44:22Made available in DSpace on 2020-08-27T00:51:32Z (GMT). No. of bitstreams: 2
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Previous issue date: 2020-05-13Embargo set by: Seth Robbins for item 115961
Lift date: 2022-08-27T00:51:40Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemAuthor requested closed access (OA after 2yrs) in Vireo ETD systemLimite
Multiple Detection and Tracking of Multi Class Vehicles using Locality Sensitive Histogram.
No full textAbstract: Multiple object detection and tracking in a cluttered background is most important in vision-based applications. In this paper, the goal is to develop a classifier that detects and tracks multiple objects thereby ensuring robustness and accuracy. Locality Sensitive Histogram feature extraction is used, which adds contributions from all the pixels in an image. These features extracted are trained using decision tree classifier which performs with an accuracy of 97%. Experimental results demonstrate the objects tracked and detected under different scale and pose variations. Evaluation and comparison of the proposed method with various other techniques is performed using performance parameters. Results depict that the proposed technique outperforms with increased accuracy and is the top performer.Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
© Copyright: All rights reserved
Replication Data for: Cash Is King: The Role of Financial Infrastructure in Digital Adoption
No full textThese files contain the replication codes and pseudo data files for the RCFS paper “Cash is King: The Role of Financial Infrastructure”, co-authored by Bhavya Agarwal, Nirupama Kulkarni, and S. K. Ritadhi
World Literature and the Case of Joyce, Rao, and Borges
No full textIn her article World Literature and the Case of Joyce, Rao, and Borges Bhavya Tiwari discusses the work of James Joyce and poses the question why Joyce is considered an important figure in Latin America and South Asia. Have Indian languages (e.g., Bengali and Hindi) responded differently to Joycean aesthetics? If yes, can there be political reasons behind this difference? Joyce\u27s own position in Europe as a modernist aesthetician complicates his reception in the periphery, India and Latin America. Hence, Tiwari queries as to what happens when Joyce\u27s texts are received on two different continents. In this context, Tiwari discusses Joyce\u27s Ulysses (1922), Raja Rao\u27s Kanthapura (1938), and Jorge Luis Borges\u27s texts with regard to their linguistic innovations and word play. Tiwari\u27s comparative and contextual analysis is meant to illustrate the relevance of comparative cultural study
Home-grown environmental aesthetics for North India
No full textEnvironmental aesthetics is a relatively new field of study. It is concerned with how human beings experience their environment through the senses, mostly in a pleasing manner. Neha Khetrapal and Bhavya Chhabra show that moving beyond a Eurocentric focus and evoking culturally familiar aesthetics can be an effective way of getting people in the global South to absorb messages around climate change. Their discussion draws on their work carried out in Prayagraj, one of the holiest cities in India
Preventing Failures by Dataset Shift Detection in Safety-Critical Graph Applications
No full textDataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes
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