Abstract

Earthquake problems in India need no introduction. From recent earthquakes, it is very well understood that lack of awareness is one of the contributing factors for huge casualty losses. In order to increase the awareness about the effects of earthquakes among professionals involved in construction, it is necessary to make them understand the concepts of structural dynamics and earthquake engineering. To address this issue, we have developed a software tool named Virtual Structural Dynamics Laboratory. Using this tool, a person with some knowledge of structural engineering can be able to learn by himself the fundamentals of structural dynamics. For convenience in explaining the concepts, we divided this tool into four modules. Each module contains few experiments with good G.U.I. In these experiments, user can find the explanation with graphical diagram. At the end of fourth module user can understand the dynamic behavior of the structure. This software tool aims to help students, architects and civil engineers in understanding the principles of structural dynamics.

Abstract

Natural disasters like earthquake, landslide, flood, drought, cyclone, forest fire, volcanic eruption are quite common in different parts of the globe. These natural disasters lead to the loss of life, property damage and socio-economic disruption. Earthquakes are one of the worst among the natural disasters. Seismic zonation map given in IS 1893:2002 shows that India is highly vulnerable for earthquake and over 60% of India is prone to moderate to major earthquakes. During past century, India has witnessed more than 650 earthquakes of magnitude greater than 5 and during past 15 years, 6 earthquakes of magnitude over 6. From recent earthquakes, it is very well understood that lack of awareness is one of the contributing factors for huge casualty losses. In order to increase the awareness about the effects of earthquakes among professionals involved in construction, it is necessary to make them understand the concepts of structural dynamics and earthquake engineering. For this, we have developed a software tool called “Interactive Structural Dynamics Learning Kit (ISDLK)” for explaining structural dynamics in a simple manner. For convenience in explaining the concepts, we divided the tool into six modules. Each module contains few experiments with good G.U.I. In these modules, user can input the value and he/she can find the desired results with explanation using graphical diagram. At the end of sixth module, user can understand the complete dynamic behavior of a structure. ISDLK aims to help students, architects and design professional in understanding structural dynamics.

Abstract

Earthquake, now everyone is familiar with this word. We have clearly witnessed during the recent Sumatra, Indonesia earthquake (M 9.0) the amount of damage an earthquake can cause to the society. Had this earthquake occurred on land, it would have easily damaged few hundreds of kilometers and the damage estimates would have been unimaginable. Earthquakes are not new to our country. We have had the long history of earthquake occurrences. Some of the major earthquakes of the world occurred in our country and neighborhood areas. During past 15 years also we have witnessed 6 moderate earthquakes: Bihar-Nepal border (M6.4) in 1988, Uttarkashi, Uttaranchal (M6.6) in 1991, Latur, Maharastra (M6.3) in 1993, Jabalpur, Madhya Pradesh (M6.0) in 1997, Chamoli, Uttaranchal (M6.8) in 1999 and Bhuj, Gujarat (M6.9) in 20011). These earthquakes caused around 40,000 casualties (see Table 1) and innumerable property loss. These events occurred with a time gap of 2 ~ 3 years. Are we ready to face another event?

Abstract

India has witnessed 6 earthquakes during past 15 years causing around 40,000 casualties and immense property loss. More than 90% of these casualties are due to collapse of buildings and they occurred within very short period of time after the earthquake. Hence, for reducing casualty losses and subsequent consequences due to earthquake, it is very important to study the response of structures due to seismic excitations. For studying the response of the structures and consequent issues after the earthquake disaster, information technology can play a major role. This paper contributes to understand the importance of information technology in earthquake disaster mitigation

Abstract

Multilingual speech recognition system is required for tasksthat use several languages in one speech recognition application. In thispaper, we propose an approach for multilingual speech recognition byspotting consonant-vowel (CV) units. The important features of spottingapproach are that there is no need for automatic segmentation of speechand it is not necessary to use models for higher level units to recognisethe CV units. The main issues in spotting multilingual CV units are thelocation of anchor points and labeling the regions around these anchorpoints using suitable classifiers. The vowel onset points (VOPs) have beenused as anchor points. The distribution capturing ability of autoassocia-tive neural network (AANN) models is explored for detection of VOPsin continuous speech. We explore classification models such as supportvector machines (SVMs) which are capable of discriminating confusableclasses of CV units and generalisation from limited amount of trainingdata. The data for similar CV units across languages are shared to trainthe classifiers for recognition of CV units of speech in multiple languages.We study the spotting approach for recognition of a large number of CVunits in the broadcast news corpus of three Indian languages

Abstract

In this paper, we present studies on combining evidence from multiple classifiers to recognize a large number of consonant-vowel (CV) unit.s of speech. Multiple classi­fier systems may lead to a better solution to the complex speech recognition tasks, when the evidence obtained from individual systems is complementary in nature. Hidden Markov models (HIvlMs) are based on the max­imum likelihood (ML) approach for training CV pat­terns of variable lengt.h. Support vector machine (SVM) models are based on discriminative learning approach for training fixed length CV patterns. Because of the differences in the training methods and in the pattern representation used, they may provide complementary evidence for CV classes. Complement.ary evidence avail­able from these classifiers is combined using the sum rule. Effectiveness of the multiple classifier system is demonstrated for recognition of CV units of speech in Indian languages .

Abstract

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Abstract

Joins on set-valued attributes (set joins) have numerous database applications. In this paper we propose PRETTI (PREfix Tree based seT joIn) – a suite of set join algorithms for containment, overlap and equality join predicates.Our algorithms use prefix trees and inverted indices. These structures are constructed on-the-fly if they are not already precomputed. This feature makes ouralgorithms usable for relations without indices and when joining intermediate results during join queries with more than two relations. Another feature of ouralgorithms is that results are output continuously during their execution and notjust at the end. Experiments on real life datasets show that the total executiontime of our algorithms is significantly less than that of previous approaches, even when the indices required by our algorithms are not precomputed.

Abstract

In view of technology/extension gaps in Indian agriculture and to exploit ICT revolution, International Institute of Information Technology, Hyderabad, A.P., India had developed eSagu model of extension system and implemented it for the cotton crop in three villages of Oorugonda, Gudeppad and Oglapur covering 749 farmers and 1041 farms during 2004-05 crop season. The main objective is to build a cost effective and scalable agricultural expert advice dissemination system to all the farmers. The three-tier system consists of farmers as end users, coordinators as intermediaries to obtain crop status through digital photographs and text and communicate the advice to the farmers. The scientists with knowledge system prepare farm advices. The evaluation study clearly brings out the feasibility and acceptability of ICT based model of eSagu. The crop status, the zooming facility of digital photographs, weather data, crop history, soil data, all have enabled the scientists in advice making and prediction. The advices were provided to the farmers in 24-36 hours. eSagu operation has improved the access, knowledge and technology adoption rate as compared to their counter parts in non-project area. It further established that the acquired technology has been quite useful and reflected in increased production by 1.5 quintals per acre, saved fertilizers by 0.76 bags, pesticides by 2.3 sprays per acre. This has resulted in a net gain of Rs. 3820.0 per acre. Farmers’ response to the utility of the project is quite positive and they want the project to continue in the future. In conclusion, the evaluation study reveals that accomplishments of the project are impressive, the system is generally accepted and throws a promise for wider application in the future.

Abstract

The growing trend towards commercial crops with ever changing technology packages necessitate a transformation in the existing agricultural extension system with emerging technologies like IT.In this context IIIT , Hyderabad has developed and implemented eSagu, a Web Based Agricultural Expert Advice Dissemination System in Atmakur mandal, Warangal district during 2004-05 covering 1,051 cotton farms. eSagu system of extension has succeeded in acquisition of infrastructure and human resources as envisaged and proved its organizational ability in coordinating different branches for a smooth functioning on proposed lines. Wholistic information in the form of clear images of crop (through digital photographs and zooming) and other information i.e. soil, weather, crop history has helped scientists to provide effective advice. The system was able to offer collective expert advice from one place with in 24 hours of response time to the farmers at the other end. Further, it is only the information that moved, while the farmers and scientists remained at their respective working places. The system has proved its technical efficiency in terms of pest identification and prediction with appropriate advices based on IPM practices to all sections of farmers. In the process of information dissemination, the system was able to provide 20,000 advices and accumulated 1,11,000 crop photographs in a period of one year. In the field of research it was able to identify new pests like stem borer and early detection of Gray Mildew disease and share the information with other research agencies. As an experiment, the project has tested feasibility and acceptability of IT for tapping its potential as an alternative to the existing extension system. It also offers scope for further reduction in the cost of delivery of advice provided a cluster based approach is adopted in the future