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 root-mean-square difference (PRD %), energy retained (Er) and Peak Signal to Noise Ratio (PSNR). Based on testing results, a comparison between the three techniques is presented. CR in the three techniques is the same and has the largest value in the 2nd level of 3-D. The hybrid
technique has the highest PSNR values in the 1st and 2nd level of 3-D and has the lowest values of (PRD %). so, the 3-D 2-level hybrid is the best technique for image compression
Abstract
β-thalassemia major is a genetic disease that causes sever defect in normal hemoglobin synthesis. The patients with β-thalassemia major need periodic blood transfusions that can result in accumulation of body iron, so treatment with iron chelating agent is required. Complications of this iron overload affecting many vital organs, including the liver. The aim of this work was to evaluate liver enzymes in β -thalassemia major patients with deferasirox versus without it. Two groups of β-thalassemia major patients were involved in this study named group A; 40 β-thalassemia patients of blood transfusion dependent without deferasirox, group B; 40 β-thalassemia patients of blood transfusion dependent on de
... Show MoreWe consider the problem of calibrating range measurements of a Light Detection and Ranging (lidar) sensor that is dealing with the sensor nonlinearity and heteroskedastic, range-dependent, measurement error. We solved the calibration problem without using additional hardware, but rather exploiting assumptions on the environment surrounding the sensor during the calibration procedure. More specifically we consider the assumption of calibrating the sensor by placing it in an environment so that its measurements lie in a 2D plane that is parallel to the ground. Then, its measurements come from fixed objects that develop orthogonally w.r.t. the ground, so that they may be considered as fixed points in an inertial reference frame. Moreov
... Show MoreOne of the principle concepts to understand any hydrocarbon field is the heterogeneity scale; This becomes particularly challenging in supergiant oil fields with medium to low lateral connectivity and carbonate reservoir rocks.
The main objectives of this study is to quantify the value of the heterogeneity for any well in question, and propagate it to the full reservoir. This is a quite useful specifically prior to conducting detailed water flooding or full field development studies and work, in order to be prepared for a proper design and exploitation requirements that fit with the level of heterogeneity of this formation.
Microalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD5, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was
... Show MoreComputer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc
... Show MoreECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.
A solid Phase Extraction (SPE) cartridges followed by HPLC-UV method is described for the simultaneous quantitative determination of benzidine (BZ) and its substituted 3, 3’-dichlorobenzidine (DCB) and 3, 3’-Dimethylbenzidine (DMB). The Benzidines were separated by liquid chromatography using a C-18 column with UV detector at wave length of 280nm. The mode of Flow was isocratic. The mobile phase was consisted of 75:25 methanol: water, column temperature 50C°, and Flow Rate 1.8ml/min. Calibration curves were linear (R2 = 0.9979-0.9995). LOD (26.36-33.67) µg/L, LOQ (109.98-186.11) µg/L, the Robustness (2.99-4.35), Ruggedness (2.93-3.65).Conditions of extraction by (SPE) cartridges were optimized, the resin used is Octadecyl silica (ODS
... Show MoreWith wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS). The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN. It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show
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