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Simulation of field trial structuresHuat, Bujang bin Kim January 1991 (has links)
No description available.
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Effects of combination motions on cylinders in waves and currentsZhou, Chao Ying January 1994 (has links)
No description available.
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Some factors affecting the performance of draught buffaloes in wetland rice cultivation in Sri LankaHulangamuwa, Sarath M. January 1993 (has links)
No description available.
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The behaviour of thin walled pipes in trenchesBueno, Benedito de Souza January 1987 (has links)
No description available.
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The effect of additional reinforcement on time-dependent behaviour of partially prestressed concreteChouman, Mustapha M. January 1990 (has links)
No description available.
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Harmonic response of transmission systems with reactive compensationSatapathy, J. K. January 1988 (has links)
No description available.
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Environmental load versus concrete quality : prediction of structure's design lifeYusof, Norzan Mohd January 1994 (has links)
No description available.
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Non-linear viscoelastic strain analysis for engineering polymersChaikittiratana, Arisara January 2000 (has links)
No description available.
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A resource aware distributed LSI algorithm for scalable information retrievalLiu, Yang January 2011 (has links)
Latent Semantic Indexing (LSI) is one of the popular techniques in the information retrieval fields. Different from the traditional information retrieval techniques, LSI is not based on the keyword matching simply. It uses statistics and algebraic computations. Based on Singular Value Decomposition (SVD), the higher dimensional matrix is converted to a lower dimensional approximate matrix, of which the noises could be filtered. And also the issues of synonymy and polysemy in the traditional techniques can be overcome based on the investigations of the terms related with the documents. However, it is notable that LSI suffers a scalability issue due to the computing complexity of SVD. This thesis presents a resource aware distributed LSI algorithm MR-LSI which can solve the scalability issue using Hadoop framework based on the distributed computing model MapReduce. It also solves the overhead issue caused by the involved clustering algorithm. The evaluations indicate that MR-LSI can gain significant enhancement compared to the other strategies on processing large scale of documents. One remarkable advantage of Hadoop is that it supports heterogeneous computing environments so that the issue of unbalanced load among nodes is highlighted. Therefore, a load balancing algorithm based on genetic algorithm for balancing load in static environment is proposed. The results show that it can improve the performance of a cluster according to heterogeneity levels. Considering dynamic Hadoop environments, a dynamic load balancing strategy with varying window size has been proposed. The algorithm works depending on data selecting decision and modeling Hadoop parameters and working mechanisms. Employing improved genetic algorithm for achieving optimized scheduler, the algorithm enhances the performance of a cluster with certain heterogeneity levels.
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A probabilistic approach to the response of slender compliant offshore structuresAkrigg, J. January 1987 (has links)
No description available.
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