Abstract

In this paper, we consider the problem of finding the k most similar objects given a query object, in large multimedia datasets. We focus on scenarios where the similarity measure itself is not fixed, but is continuously being refined with user feedback. Conventional database techniques for efficient similarity search are not effective in this environment as they take a specific similarity/distance measure as input and build index structures tuned for that measure. Our approach works effectively in this environment as validated by the experimental study where we evaluate it over a wide range of datasets. The experiments show it to be efficient and scalable. In fact, on all our datasets, the response times were within a few seconds, making our approach suitable for interactive applications.

Abstract

A multiple film based daylight control system for window has been developed to maintain the illuminance level at task plane. The developed system consists of three films with a visual transmittivity (Tvis) range of 0.159-0.015 and a 2x55W dimmable compact fluorescent lamp (CFL) fixture. The system works on the principle of feedback control, which records the changes in light intensity with the help of photosensor placed on the ceiling and facing the task plane and accordingly adjusts the film-position as well as the control voltage of dimmable CFL to maintain the task plane illuminance within a tolerance of-10%,+ 20% of setpoint. Optimized use of solar illuminance saves energy used for the task lighting for the period from 8: 00 to 19: 00, which was found to be about 70%. The paper describes the design, implementation of the proposed system and the preliminary results for task light illuminance and energy savings achieved in laboratory setup.

Abstract

A read-only transaction (ROT) does not modify any data. The main issues regarding processing ROTs are correctness, data currency and perform-ance. Two-phase Locking (2PL) protocol is widely used for concurrency con-trol with serializabilty as correctness criteria. Even though 2PL processes ROTs correctly with no data currency related issues, the performance deteriorates as data contention increases. To improve the performance over 2PL, snapshot iso-lation (SI)-based protocols have been proposed. SI-based protocols process ROTs by reading from a snapshot of the committed data and ignoring the modi-fications produced by the concurrent active transactions. Even though SI-based algorithms improve the performance of ROTs, both data currency of ROTs and correctness (serializability) are compromised. In this paper, we propose an ap-proach to improve the performance of ROTs using speculation without compromising data currency of transactions and correctness. The proposed approach improves the performance of ROTs by trading extra computing re-sources without violating serializability as correctness criteria. The simulation results show that with the proposed protocol the throughput performance is im-proved significantly over 2PL and SI-based approaches with manageable extra resources.

Abstract

In this paper, we explain a personalized agricultural advisory system called eSagu, which has been developed to improve the performance and utilization of agriculture technology and help Indian farmers. In eSagu, rather than visiting the crop in person, the agricultural expert delivers the expert advice at regular intervals (once in one or two weeks) to each farm by getting the crop status in the form of digital photographs and other information. During 2004-06, through eSagu, agricultural expert advices delivered for about 6000 farms covering six crops. The results show that the expert advices helped the farmers to achieve savings in capital investment and improved the crop yield. Mainly, the data warehouse of farm histories has been developed which is providing the crop related information to the agricultural expert in an integrated manner for generating a quality agricultural expert advice. In this paper, after explaining eSagu and its advantages, we discuss how data warehouse of farm histories is enabling agricultural expert to deliver a quality expert advice. We also discuss some research issues to improve the performance of eSagu.

Abstract

A read-only transaction (ROT) does not modify any data. The main issues regarding processing ROTs are correctness, data currency and performance. Two-phase Locking (2PL) protocol is widely used for concur-rency control with serializabilty as correctness criteria. Even though 2PL processes ROTs correctly with no data currency related issues, the performance deteriorates as data contention increases. To improve the performance, an approach has been proposed in the literature by considering “Snapshot Isolation (SI)” as correctness criteria to process ROTs. At SI-level, ROTs are processed by reading from a snapshot of the committed data and ignoring the modifications produced by the concurrent active transactions. Even though SI-based algorithms improve the performance of ROTs, data currency of ROTs and correctness (serializability) are compromised. In this paper, we propose an approach by extending the notion of speculation to improve the performance of ROTs without com-promising data currency of transactions and correctness. Speculation-based approach improves the performance of ROTs by trading extra computing resources without violating serializability as correctness criteria. The simula-tion results show that with the proposed protocol the throughput performance is improved significantly over 2PL and the data currency of ROTs is improved significantly over SI-based ap proaches with manageable extra re-sources.

Abstract

This paper presents the experiments of Language Technologies Research Centre (LTRC) 1 as part of their participation in CLEF2 2007 Indian language to English ad-hoc cross language document retrieval task. In this paper we discuss our Hindi and Telugu to English CLIR system and the experiments using CLEF 2007 dataset. We used a variant of TFIDF algorithm in combination with a bilingual lexicon for query translation. We also explored the role of a document summary in fielded queries and two different boolean formulations of query translations. We find that a hybrid boolean formulation using a combination of boolean AND and boolean OR operators improves ranking of documents. We also find that simple disjunctive combination of translated query

Abstract

This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We argue that the recognition scheme for a book could be considerably different from that designed for isolated pages. We employ learning procedures to capture the relevant information available online, and feed it back to update the knowledge of the system. Experimental results show the effectiveness of our design for improving the performance on-the-fly.

Abstract

This paper presents an efficient indexing and retrieval scheme for searching in document image databases. In many non-European languages, optical character recognizers are not very accurate. Word spotting - word image matching - may instead be used to retrieve word images in response to a word image query. The approaches used for word spotting so far, dynamic time warping and/or nearest neighbor search, tend to be slow. Here indexing is done using locality sensitive hashing (LSH) - a technique which computes multiple hashes - using word image features computed at word level. Efficiency and scalability is achieved by content-sensitive hashing implemented through approximate nearest neighbor computation. We demonstrate that the technique achieves high precision and recall (in the 90% range), using a large image corpus consisting of seven Kalidasa’s (a well known Indian poet of antiquity) books in the Telugu language. The accuracy is comparable to using dynamic time warping and nearest neighbor search while the speed is orders of magnitude better - 20000 word images can be searched in milliseconds.

Abstract

Software engineering (SE) educators have been advocating the use of non-conventional approaches for SE education since long. In this context, we conducted action-research to compare the effectiveness of a case study approach with conventional lecture based approach. We designed and taught a first course in SE, that involved case study approach as well as the traditional lecture based approach. We recorded and analyzed student's perception of learning over using well defined parameters that reconciled with cognitive, skills and metacognitive goals of SE education. Results corroborated that case study approach is more effective and interesting for learning SE than the lecture based approach. These results indicate that academia and industry should further explore learning-by-doing paradigm, specially the case studies. Benefits of approach include bridging of the industry- academia gap and creation of professionals who are well versed with theory and practice and have experienced the intricacies of real software development even before entering the industry. This paper provides empirical data to support that case study approach is very effective in SE education and hence useful for curriculum designers. This work is useful for SE educators and researchers as it describes methodology for rigorous scientific educational researc

Abstract

This paper explores the possibility of using convex optimization to address a class of problems in visual servoing. This work is motivated by the recent success of convex optimization methods in solving geometric inference problems in computer vision. We formulate the visual servoing problem with feature visibility constraints as a convex optimization of a function of the camera position i.e. the translation of the camera. First, the path is planned using potential field method that produces unconstrained but straight line path from the initial to the desired camera position. The problem is then converted to a constrained convex optimization problem by introducing the visibility constraints to the minimization problem. The objective of the minimization process is to find for each camera position the closest alternate position from which all features are visible. This algorithm ensures that the solution is optimal. This formulation allows the introduction of more constraints, like joint limits of the arm, into the visual servoing process. The results have been illustrated in a simulation framework.