Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Optimizing set of paths connecting multiple source-sink pairs(Institute of Electrical and Electronics Engineers Inc., 2017) Agrawal, A.; Dixit, B.; Karve, V.U.; Chandavarkar, B.R.In this paper we aim to propose an algorithm for finding the most optimal path with some must-include nodes. The algorithm will be used to look for the best path that includes all the required nodes arranged in static topology in the most cost efficient way while keeping in mind the given constraint. We have developed the algorithm for nodes, where information about all nearby nodes is available beforehand. The main aim of the algorithm is to get the optimal paths between nodes with the given constraints. After getting all optimal paths, the algorithm will use a heuristic function to determine the best path out of the all paths as the final path. The main aim of our proposed methodology is to minimize the input resources to achieve the maximum output. For doing this we have proposed a method to combine multiple paths from a source to sink in one single optimal path, thus reducing the number of paths and achieving the same output. For developing this algorithm we have used concepts of graph theory, combinatorial optimizations and well known approach of Knuth for finding exact cover for given graph. © 2016 IEEE.Item Physical, mechanical and sliding wear behavior of solid glass microsphere filled epoxy composites(Elsevier Ltd, 2018) Agrawal, A.; Chandraker, S.; Sharma, A.Performance of epoxy based composites filled with micro-size solid glass microsphere (SGM) is reported in this work. The main emphasis of the present work is on the common trends detected in properties of epoxy/SGM composites. For physical property, densities of all the fabricated samples were presented.Glass micro-sphere filled epoxy composites haveless porosity. They also exhibit improvedmicro-hardness, flexural and impact strength, though tensile strength is compromised marginally. Further, sliding wear performance of the fabricated composites with respect to filler content, sliding velocity and applied force were studied.With improved physical, mechanical and sliding wear, the presently fabricated composites found its potential application where wear predominated. © 2018 Elsevier Ltd. All rights reserved.Item When and where?: Behavior dominant location forecasting with micro-blog streams(IEEE Computer Society, 2018) Gautam, B.; Annappa, B.; Singh, A.; Agrawal, A.The proliferation of smartphones and wearable devices has increased the availability of large amounts of geospatial streams to provide significant automated discovery of knowledge in pervasive environments, but most prominent information related to altering interests have not yet adequately capitalized. In this paper, we provide a novel algorithm to exploit the dynamic fluctuations in user's point-of-interest while forecasting the future place of visit with fine granularity. Our proposed algorithm is based on the dynamic formation of collective personality communities using different languages, opinions, geographical and temporal distributions for finding out optimized equivalent content. We performed extensive empirical experiments involving, real-time streams derived from 0.6 million stream tuples of micro-blog comprising 1945 social person fusion with graph algorithm and feed-forward neural network model as a predictive classification model. Lastly, The framework achieves 62.10% mean average precision on 1,20,000 embeddings on unlabeled users and surprisingly 85.92% increment on the state-of-the-art approach. © 2018 IEEE.Item ARS NITK at MEDIQA 2019: Analysing various methods for natural language inference, recognising question entailment and medical question answering system(Association for Computational Linguistics (ACL), 2019) Agrawal, A.; George, R.A.; Ravi, S.S.; Kamath S․, S.S.; Anand Kumar, M.A.This paper includes approaches we have taken for Natural Language Inference, Question Entailment Recognition and Question-Answering tasks to improve domain-specific Information Retrieval. Natural Language Inference (NLI) is a task that aims to determine if a given hypothesis is an entailment, contradiction or is neutral to the given premise. Recognizing Question Entailment (RQE) focuses on identifying entailment between two questions while the objective of Question-Answering (QA) is to filter and improve the ranking of automatically retrieved answers. For addressing the NLI task, the UMLS Metathesaurus was used to find the synonyms of medical terms in given sentences, on which the InferSent model was trained to predict if the given sentence is an entailment, contradictory or neutral. We also introduce a new Extreme gradient boosting model built on PubMed embeddings to perform RQE. Further, a closed-domain Question Answering technique that uses Bi-directional LSTMs trained on the SquAD dataset to determine relevant ranks of answers for a given question is also discussed. Experimental validation showed that the proposed models achieved promising results. © 2019 Association for Computational LinguisticsItem Leveraging multimodal behavioral analytics for automated job interview performance assessment and feedback(Association for Computational Linguistics (ACL), 2020) Agrawal, A.; George, R.A.; Ravi, S.S.; Kamath S․, S.; Anand Kumar, M.Behavioral cues play a significant part in human communication and cognitive perception. In most professional domains, employee recruitment policies are framed such that both professional skills and personality traits are adequately assessed. Hiring interviews are structured to evaluate expansively a potential employee’s suitability for the position - their professional qualifications, interpersonal skills, ability to perform in critical and stressful situations, in the presence of time and resource constraints, etc. Therefore, candidates need to be aware of their positive and negative attributes and be mindful of behavioral cues that might have adverse effects on their success. We propose a multimodal analytical framework that analyzes the candidate in an interview scenario and provides feedback for predefined labels such as engagement, speaking rate, eye contact, etc. We perform a comprehensive analysis that includes the interviewee’s facial expressions, speech, and prosodic information, using the video, audio, and text transcripts obtained from the recorded interview. We use these multimodal data sources to construct a composite representation, which is used for training machine learning classifiers to predict the class labels. Such analysis is then used to provide constructive feedback to the interviewee for their behavioral cues and body language. Experimental validation showed that the proposed methodology achieved promising results. © 2017 Association for Computational LinguisticsItem Mechanical and Thermal Behaviour of Epoxy/Hexagonal Boron Nitride/Short Sisal Fiber Hybrid Composites(Institute of Physics Publishing helen.craven@iop.org, 2020) Agrawal, A.; Chandraker, S.; Sharma, A.Hybrid composite i.e. surface modified hexagonal boron nitride (hBN) and short sisal fiber reinforced in epoxy matrix is fabricated using hand lay-up method. The effect of surface modified hBN filler and sisal fiber content on mechanical and thermal properties of epoxy based hybrid composites were investigated in this paper. The main aim of the investigation is to develop a material which can found its application in microelectronic components. As per the requirement of microelectronic industry, the material should possess high thermal conductivity. Hence, thermal conductivity of epoxy increases with increase in hexagonal boron nitride content. Inspite of insulative nature of sisal fiber, the study shows that its inclusion in combination with hBN enhances the thermal conductivity if the content of both the fillers were properly selected. Other thermal property like coefficient of thermal expansion and glass transition temperature appreciably improves when combination of fillers were added in epoxy matrix. Mechanical properties under study i.e. tensile strength and compressive strength also enhances when combination of sisal fiber and hBN were incorporated as compared to when single filler hBN were used. Hence, usage of hybrid filler as reinforcement in epoxy improve overall mechanical and thermal property of the developed material. © 2020 Published under licence by IOP Publishing Ltd.Item Benchmarking semantic, centroid, and graph-based approaches for multi-document summarization(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Agrawal, A.; George, R.A.; Ravi, S.S.; Kamath S․, S.Multi-document summarization (MDS) is a pre-programmed process to excerpt data from various documents regarding similar topics. We aim to employ three techniques for generating summaries from various document collections on the same topic. The first approach is to calculate the importance score for each sentence using features including TF-IDF matrix as well as semantic and syntax similarity. We build our algorithm to sort the sentences by importance and add it to the summary. In the second approach, we use the k-means clustering algorithm for generating the summary. The third approach makes use of the Page Ranking algorithm wherein edges of the graph are formed between sentences that are syntactically similar but are not semantically similar. All these techniques have been used to generate 100–200 word summaries for the DUC 2004 dataset. We use ROUGE scores to evaluate the system-generated summaries with respect to the manually generated summaries. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.Item Physical and mechanical properties of epoxy reinforced with pistachio shell particulates(American Institute of Physics Inc., 2021) Chandraker, S.; Agrawal, A.; Prakash, P.; Khan, I.A.; Sharma, A.Recently, natural fillers have gain huge interest among the academic researchers and scientists to be used as potential reinforcement material in polymeric matrix composites. The various reasons which attract the scientific community toward it usage in polymer composites are its low cost, ample availability, easy processing and the most important is the growing concern towards environmental awareness as they are bio-degradable. Reinforcing natural fillers is also an efficient approach towards waste management as most of the promising natural fillers were dumped if not used. Following the similar trend, an attempt has been made to utilize pistachio shells as a filler material in polymeric resin for developing a composite body. Pistachio shell with particle size 75 micron is used with epoxy matrix in present investigation. Six sets of epoxy based composites are fabricated using hand lay-up method by varying the filler content upto 30 wt. %. Density of the composites is evaluated using Archimedes principle. Micrographs are taken to visualize the compatibility between filler and matrix body. Tensile strength, compressive strength, flexural strength and hardness are the various mechanical properties evaluated of the developed materials. From the experimental analysis, it has been found that, all the mechanical properties of the composite under consideration increases with filler content. Though increase in density is also observed with filler loading but the increment is marginal. On the basis of experimental findings, it can be concluded that the developed material can be gainfully found its application in light duty structures. © 2021 Author(s).Item Room temperature sliding wear behavior of Ti6Al4V: A review(American Institute of Physics Inc., 2021) Sreesha, R.B.; Kumar, D.; Chandraker, S.; Agrawal, A.High strength-to-weight ratio, high temperature stability, and bio-compatibility makes Ti6Al4V alloy an interesting choice for aerospace, automobile, chemical, and bio-medical industries. In spite of the several attractive properties, the application of the alloy is restricted in sliding interfaces. As a result, many studies, involving surface modifications of the alloy or the tribo-pair in general have surfaced for improvement in tribological properties. The details of tribological behavior of un-modified Ti6Al4V alloy in various operating and environmental conditions, can act as an initial data for the future researches aimed at improving its tribological properties. Thus, the present review is an attempt to put together the studies conducted to evaluate the sliding wear behavior of Ti6Al4V in both dry and lubricated condition at the room temperature. © 2021 Author(s).Item Advancements in Financial Document Structure Extraction: Insights from Five Years of FinTOC (2019-2023)(Institute of Electrical and Electronics Engineers Inc., 2023) Kang, J.; Patel, M.M.; Agrawal, A.; Simhadri, S.; Srinivasa, R.; Bellato, S.; Anand Kumar, M.; Tsang, N.D.; El-Haj, M.In this comprehensive paper, we present a detailed overview of the Financial Table Of Content extraction shared task series, FinTOC, conducted over a span of five years from 2019 to 2023. This paper serves as a retrospective analysis of the key developments in the field of financial document structure extraction. The FinTOC series, hosted within the framework of the Financial Narrative Processing (FNP) workshop, has been instrumental in shaping the landscape of Natural Language Processing (NLP) in the financial domain. Our analysis delves into the diverse methodologies proposed by participants across all editions, shedding light on the innovative strategies employed to tackle the intricate challenge of extracting structured information from financial documents. We explore the evolution of techniques, from traditional rule-based approaches to cutting-edge deep learning models, showcasing the dynamic nature of NLP advancements. Furthermore, our study investigates the introduction of multilingual datasets by the organizers, highlighting the importance of cross-lingual analysis in financial document processing. We also examine the contributions made by participants in augmenting the training data with external sources, showcasing the collaborative spirit of the NLP community in enhancing the quality and size of the shared training dataset. © 2023 IEEE.