Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by de

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

Far infrared photoconductive detectors based on multi-wall carbon nanotubes (MWCNTs) were fabricated and their characteristics were tested. MWCNTs films deposited on porous silicon (PSi) nanosurface by dip and drop coating techniques. Two types of deposited methods were used; dip coating sand drop –by-drop methods. As well as two types of detector were fabricated one with aluminum mask and the other without, and their figures of merits were studied. The detectors were illuminated by 2.2 and 2.5 Watt from CO2 of 10.6 􀀀m and tested. The surface morphology for the films is studied using AFM and SEM micrographs. The films show homogeneous distributed for CNTs on the PSi layer. The root mean square (r.m.s.) of the films surface roughness in

Leuconostoc bacteria was isolated from local pickled cabbage (Brassica oleracea capitata) and identified as Leuconostoc mesenteroides by morphology,biochemical and physiological. The local isolated L. mesenteroides bacteria under the optimal conditions of dextran production showed that, the highly production of dextran was 7.7g achieved by using a modified natural media comprised of 100ml whey, 10g refined sugar, 0.5g heated yeast extract, 0.01g CaCl2, 0.001g MgSO4, 0.001g MnCl2 and 0.001g NaCl at pH 6 and 25̊C for 24 hr of fermentation and by using 1ᵡ106 cell/ml as initial inoculums volume. Some applications in food technology (Ice cream, Loaf, Ketchup and Beef preservation) have been performed with processed dextran. The result

Al-Yusifia river was assessed at three sampling stations with study period from Autumn 2010 to the end of Summer 2011. The present investigation was carried out on diversity of fungi and bacteria from Al-Yusifia river, Baghdad city. During the study, a total of 12 fungal genus and 6 bacterial genus were isolated during the year seasons. The dominant fungus at the three stations were Penicillium sp., then Rhizopus and Trichophyton   megninii while the dominant bacteria was Escherichia coli and Klebsiella sp.

            The higher

Chitosan-schiff base with three different ratios of para-Dimethyl aminobenzaldehyde& chitosan Schiff base hydrogels have been prepared for controlled drug release study. The synthesized chitosan Schiff base and chitosan Schiff base hydrogel were characterized by FT-IR, UV-Visible, SEM, analysis. Swelling properties of the hydrogel were investigated at three different media pH (2, 7, 10). The swelling degree varied with the pH, amount of crosslinking agent glutaraldehyde and with the amount of paraDimethylaminobenzaldehyde for the hydrogels. All hydrogels were used for controlled drug release system. Aspirin was used as model drug, in three different buffer solution (2, 7, 10) as release media. The rate of release of drugs in the pH2 is m

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD