This paper presents an architecture for the data warehouse of outpatient healthcare (DWOP) as a data repository collects data from two different sources (Databases of outpatient healthcare and Excel files from hospitals) and provides storage, functionality and responsiveness to queries to meet decision makers requirements.
Successfully supporting managerial decision-making is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. “On-Line Analytical Processing (OLAP) is utilized for decision support to get interesting information†from the data warehouse with a rapid execution time. OLAP is considered one of Business Intelligence tools.
In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r
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