In this research, a simple experiment in the field of agriculture was studied, in terms of the effect of out-of-control noise as a result of several reasons, including the effect of environmental conditions on the observations of agricultural experiments, through the use of Discrete Wavelet transformation, specifically (The Coiflets transform of wavelength 1 to 2 and the Daubechies transform of wavelength 2 To 3) based on two levels of transform (J-4) and (J-5), and applying the hard threshold rules, soft and non-negative, and comparing the wavelet transformation methods using real data for an experiment with a size of 26 observations. The application was carried out through a program in the language of MATLAB. The researcher concluded that using the wavelet transform with the Suggested threshold reduced the noise of observations through the comparison criteria.
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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Proteinases (E.C.3.4.21) family are widely distributed in the nature; it was present in animals tissues , plants and microbial cell . Protease was purified from Zahdi seed (Phoenix dactylifera L.) by several steps included ammonium sulphite ppt (75%) saturation and dialyzed against the 80mM sodium phosphate buffer at pH 7.5 . The enzyme specific activity was 407.62 unit/mg protein. The obtained extract was purified by DEAE-Cellulose column followed by gel filtration through Sephacyl S-200 column .The enzyme specific activity ,yield and purification fold were 1873.49 unit/mg protein, 22.99 and 58.42% respectively. The results of protease characterization showed that the molecular weight was 25118 daltons as determined by gel f
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Abstract: Recombinant human bone morphogenetic protein-2 (rhBMP-2) and platelet-rich fibrin (PRF) bioactive materials have been used to enhance healing and improve dental implant stability. This study aimed to compare the effect of rhBMP-2 and PRF bioactive materials on dental implant stability at different intervals and to evaluate the correlation of implant length and diameter with implant stability. Two bioactive materials were compared to evaluate their effect on dental implant stability. A total of 32 patients (102 dental implants) were divided into 3 groups: 24 dental implants with bone morphogenetic protein (BMP), 27 dental implants with PRF, and 51 dental implants without BMP or PRF (control group). Data were statistically analyzed
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