Abstract

Social media platforms, particularly Twitter, have emerged as vital media for organizing online protests worldwide. During protests, users on social media share different narratives, often coordinated to share collective opinions and obtain widespread reach. In this paper, we focus on the communities formed during a protest and the collective narratives they share, using the protest on the enactment of the Citizenship Amendment Act (#CAA) by the Indian Government as a case study. Since #CAA protest led to divergent discourse in the country, we first classify the users into opposing stances, i.e., protesters (who opposed the Act) and counter-protesters (who supported it) in an unsupervised manner. Next, we identify the coordinated communities in the opposing stances and examine the collective narratives shared by coordinated communities of opposing stances. We use content-based metrics to identify user coordination, including hashtags, mentions, and retweets. Our results suggest mention as the strongest metric for coordination across the opposing stances. Next, we decipher the collective narratives in the opposing stances using an unsupervised narrative detection framework and found call-to-action, on-ground activity, grievances sharing, questioning, and skepticism narratives in the protest tweets. We analyze the strength of the different coordinated communities using network measures, and perform inauthentic activity analysis on the most coordinated communities on both sides. Our findings also suggest that coordinated communities, which were highly inauthentic, showed the highest clustering coefficient towards a greater extent of coordination.

Abstract

Searching in scanned documents is an important problem in Digital Libraries. If OCRs are not available, the scanned images are inaccessible. In this paper, we demonstrate a searching procedure without an intermediate textual representation. We achieve effective retrieval from document databases by matching at word-level using image features. Word profiles, structural features and transform domain representations are employed for characterising the word images. A novel partial matching approach based on dynamic time warping (DTW) is proposed to take care of word form variations. With the new partial matching procedure, morphologically variant words become similar in image space. This is specially useful for grouping together similar words for indexing purpose. We extend our formulation for cross-lingual search with the help of transliteration.

Abstract

This paper presents a novel approach for retrieval of relevant documents from a large collection of printed document images, where search in corresponding textual content is practically impossible due to the unavailability of robust OCRs. We achieve effective search by matching at wordlevel using image features. Importance of a document for a given query is also computed at image-level.

Abstract

Annotated datasets of handwriting are a prerequisite for the design and training of handwriting recognition algorithms. In this paper, we briefly describe an XML representation for annotation of online handwriting data that uses the emerging Digital Ink Markup Language (InkML) standard from W3C for the representation of handwriting data. We then describe a tool based on the proposed representation that can be used for annotation of digital ink. Ease and speed of annotation are emphasized in the design of the tool. Together, the representation and the tool attempt to address the requirements of creation of annotated datasets of handwritten data in different scripts around the worldwid

Abstract

This paper presents several results on images of various configurations of conics. We extract information about the plane from single and multiple views of known and unknown conics, based on planar homography and conic correspondences. We show that a single conic section cannot provide sufficient information. Metric rectification of the plane can be performed from a single view if two conics can be identified to be images of circles without knowing their centers or radii. The homography between two views of a planar scene can be computed if two arbitrary conics are identified in them without knowing anything specific about them. The scene can be reconstructed from a single view if images of a pair of circles can be identified in two planes. Our results are simpler and require less information from the images than previously known results. The results presented here involve univariate polynomial equations of degree 4 or 8 and always have solutions. Applications to metric rectification, homography calculation, 3D reconstruction, and projective OCR are presented to demonstrate the usefulness of our scheme

Abstract

There has been an increasing need to find effective ways to impart Software Engineering Education. This paper discusses the problems the different approaches, both conventional and non conventional, face and proposes a case study approach that addresses these issues. This research aims to create a teaching methodology that will assist the teachers to create an effective learning environment and help the students to gain realistic exposure to concepts of Software Engineering as they are applied in the real world. The focus of the paper is to emphasize on creating a context to learn Software Engineering through case studies that imbibe the best practices from real world experiences.

Abstract

n this paper, we have proposed speculative locking (SL) protocols to improve the performance of distributed databasesystems (DDBSs) by trading extra processing resources. In SL, a transaction releases the lock on the data object whenever itproduces corresponding after-image during its execution. By accessing both before and after-images, the waiting transaction carriesout speculative executions and retains one execution based on the termination (commit or abort) mode of the preceding transactions.By carrying out multiple executions for a transaction, SL increases parallelism without violating serializability criteria. Under the naiveversion of SL, the number of speculative executions of the transaction explodes with data contention. By exploiting the fact that asubmitted transaction is more likely to commit than abort, we propose the SL variants that process transactions efficiently bysignificantly reducing the number of speculative executions. The simulation results indicate that even with manageable extraresources, these variants significantly improve the performance over two-phase locking in the DDBS environments where transactionsspend longer time for processing and transaction-aborts occur frequently.

Abstract

In this papcr, wc propose an approach for continuous speech recognition by spotting consonant-vowel (CV) units. The niain issues in spotting CV units are the location of anchor points and labelling the regions around these anchor points using suitable classifiers. The vowel onset points (VOPs) trave bcen used as an- chor points. The distribution capturing ability of autoassociative neural network (AA”) models is explored for detection of VOPs in continnous speech. We consider support vector machine (SVM) based classifiers due to their ability of generalisation from limited training data and also due to their inherent discriminative learn- ing. The CV spotting approach for continuous speech recognition has bccn dcmonstratcd for scntcnccs in Indian languages

Abstract

When an active bedrock fault ruptures, the movement along the fault propagates through the overlying soil and produces zones of intense shear. If the fault movement propagates upto or near the ground surface, the damage to constructed facilities due to faulting, in conjunction with that induced by strong ground motion, can be significant. This paper contributes to the understanding of the response of soil deposits to the underlying bedrock fault displacement. In the conventional attenuation relationship, peak ground acceleration shows maximum value at the closest distance from the fault. However, in the real observations, sometimes it is found that the damage near to the surface fault is not maximum, instead it is high little away from the surface rupture zone. To understand the above-mentioned response of soil deposits, we attempted to develop a new application to Applied Element Method (AEM) by modeling the fault rupture zone. In this, we study the behavior of dip-slip faults. The effect of the slip velocity on the ground motion is studied first and then the attenuation of PGA in the near fault zone is studied. Effect of the material properties is also discussed.

Abstract

Sketch matching algorithms are commonly used for indexing and retrieval of documents based on printed or hand-drawn sketches. One could use a hand-held computer to do sketch-based queries to a database containing hand-drawn and printed sketches. We present an on-line hand-drawn sketch matching algorithm based on a line-based representation of sketches. A distance measure is defined for comparing two sketches based on this representation. The algorithm is computationally efficient and achieves a recall rate of 88.44% at the same precision, when tested on a database of 150 sketches collected from 5 users.