We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.
In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%
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Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust M method after their development through the use of sequential approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate
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Design of experiments (DOE) was made by Minitab software for the study of three factors used in the precipitation process of the Sodium Aluminate solution prepared from digestion of α-Al2O3 to determine the optimum conditions to a produce Boehmite which is used in production of ɤ-Al2O3 during drying and calcination processes, the factors are; the temperature of the sodium aluminate solution, concentration of HCl acid added for the precipitation and the pH of the solution at which the precipitation was ended. The design of the experiments leads to 18 experiments.
The results show that the optimum conditions for the precipitation of the sodium aluminate solution which
... Show MoreIn this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg
... Show MoreA new simultaneous spectrophotometric-kinetic method was developed to determine phenylephrine (PHEN) and tetracycline (TETR) via H-point standard addition method (HPSAM). The proposed procedures rely on the measurements of the difference in the rate of charge-transfer (CT) reaction between each of PHEN and TETR as electron donors with p-Bromanil (p-Br) as an electron acceptor. Different experimental factors which affect the extent of the complex formation were investigated by monitoring the value of absorbance at 446 nm. Time pair of 50 -100 sec was selected and employed, among different examined pairs since it results in the highest accuracy for HPSAM-plot. Linear calibration graphs in the concentration ranges of 10.0-40.0 and 10.0–50.0
... Show MoreThis study involved the effect of anew nickel (II) complexs with formla [NiL2(H2O)2].2.5ETOH where L=Bis[5-(p-nitrophenyL)-4-phenyL-1,2,4-traizole-3-dithocarbamato hydrazide] diaqua. nickel(II). Ethanol(2.5).and anti-cancer drug cyclophosphamide on specific actifity of two Liver enzymes (GOT,GPT) in the (Liver,kidney) tissues and on the creatinine Level in the kidney byUtilizing an invivosystem in femalmice.The result showed that inhibition in the activity of GPT and GOT enzymes in theLiver and in both nickel (II) complex and cyclophosphamide drug (CP) . mice weretreated with three doses (90,180,320) µg/mouse for three days for each group.The Liver show's the highest rate of GPT inhibition was about 97.43% at180µg/mouse regarding the ki
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The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t
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