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This paper describes enhanced subquery optimizations in Oracle relational database system. It discusses several techniques -- subquery coalescing, subquery removal using window functions, and view elimination for group-by queries. These techniques recognize and remove redundancies in query structures and convert queries into potentially more optimal forms. The paper also discusses novel parallel execution techniques, which have general applicability and are used to improve the scalability of queries that have undergone some of these transformations. It describes a new variant of antijoin for optimizing subqueries involved in the universal quantifier with columns that may have nulls. It then presents performance results of these optimizations, which show significant execution time improvements.

Iris recognition system for identity authentication and verification is one of the most precise and accepted biometrics in the world. Portable iris system mostly used in law enforcement applications, has been increasing more rapidly. The portable device, however, requires a narrow-bandwidth communication channel to transmit iris code or iris image. Though a full resolution of iris image is preferred for accurate recognition of individual, to minimize time in a narrowbandwidth channel for emergency identification, image compression should be used to minimize the size of image. This paper has investigated the effects of compression particularly for iris image based on wavelet transformed image, using Spatialorientation tree wavelet (STW), Embedded Zero tree Wavelet (EZW) and Set Partitioning in hierarchical trees (SPIHT), to identify the most suitable image compression. In this paper, Haar wavelet transform is utilized for image compression and image decomposition, by varying the decomposition level. The results have been examined in terms of Peak signal to noise ratio (PSNR), Mean square Error (MSE), Bit per Pixel Ratio (BPP)and Compression ratio (CR). It has been evidently found that wavelet transform is more effective in the image compression, as recognition performance is minimally affected and the use of Haar transform is ideally suited. CASIA, MMU iris database have been used for this purpose. Keywords-iris recognition; image compression; mean square error; peak signal to noise ratio(PSNR); wavelet decompositionI.