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.

Abstract

This paper describes a new approach for script separation. A characterlevel script separation scheme is combined with a Viterbi algorithm to get an optimal sequence of scripts which could generate such a text. This method complements the popular approaches for script separation at paragraph level using texture features or at line level using structural features.

Abstract

The blocking phenomena in two-phase commit (2PC) reduces the availability of the system as the blocked transactionskeep all the resources until the recovery of the coordinator. The three-phase commit (3PC) protocol involves an extra roundof message transmission to resolve the blocking problem. In this paper, we propose a backup commit (BC) protocol to reducethe blocking problem by attaching multiple backup sites to the coordinator site. In BC, after receiving responses from theparticipants, the coordinator quickly communicates the final decision to the backup sites, before it sends the final decision tothe participants. When blocking occurs, the participant sites can terminate the transaction by consulting a backup site of thecoordinator. The BC protocol resolves the blocking in most of the coordinator site failures without involving an expensivecommunication cycle as in 3PC. The simulation experiments indicate that the throughput performance of BC is close to 2PC.2002 Elsevier Science B.V. All rights reserved.

Abstract

Distributed locking is commonly adopted for performing concurrency control in distributed systems. It incorporatesadditional steps for handling deadlocks. This activity is carried out by methods based on wait-for-graphs or probes. The present studyexamines detection of conflicts based on enhanced local processing for distributed concurrency control. In the proposed “edgedetection” approach, a graph-based resolution of access conflicts has been adopted. The technique generates a uniform wait-forprecedence order at distributed sites for transactions to execute. The earlier methods based on serialization graph testing are difficultto implement in a distributed environment. The edge detection approach is a fully distributed approach. It presents a unified techniquefor locking and deadlock detection exercises. The technique eliminates many deadlocks without incurring message overheads

Abstract

Insect pests are a major cause of crop loss globally. Pest management will be effective and efficient if we can predict the occurrence of peak activities of a given pest. Research efforts are going on to understand the pest dynamics by applying analytical and other techniques on pest surveillance data sets. In this study we make an effort to understand pest population dynamics using Neural Networks by analyzing pest surveillance data set of Helicoverpa armigera or Pod borer on chickpea (Cicer arietinum L.) crop. The results show that neural network method successfully predicts the pest attack incidences for one week in advance.