Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce a pseudo-random number.
This study focused on the improvement of the quality of gasoline and enhancing its octane number by the reduction of n-paraffins using zeolite 5A. This study was made using batch and continuous mode. The parameters which affected the n-paraffin removal efficiency for each mode were studied. Temperature (30 and 40 ˚C) and mixing time up to 120 min for different amounts of zeolite ranging (10-60 g) were investigated in a batch mode. A maximum removal efficiency of 64% was obtained using 60 g of zeolite at 30 ˚C after a mixing time 120 min. The effect of feed flow rate (0.3-0.8 l/hr) and bed height (10-20 cm) were also studied in a continuous mode. The equilibrium isotherm study was made using different amounts of zeolite (2-20 g) and the
... Show MoreThe adoption of many mathematical concepts contributes to the construction of models of sports and the population can be interpreted to explain the movement and growth of the population lead to proper planning to manage the requirements of the population and meet their needs of providing education or providing medical services, health and others. In this study, the number of births in the Governorate of Basrah for the period (1998-2050) is estimated to be based on the assumption that the population of the visually impaired is a stable society. If the rate of growth is (0.0492), some demographic indicators are important for maintaining the average age of women at pregnancy (27.817). Each woman will give birth (3.74) female birth d
... Show MoreThe current research aims to evaluate liquidity (as an independent variable) to improve the bank’s profitability (as a dependent variable ), by the bank’s ability to maximize its profits from its business results without excessive bank’s liquidity, so that may affect negatively affects the bank’s reputation and it’s dealers confidence in facing their financial obligations. and this may lead trying to come out among other recommendations including contributing to obtain, the bank’s ability to achieve liquidity balance to maximize its profits. This research has been applied to the sample induced intentionally by choosing three Iraqi private banks. The researcher used financial indicators to assess the bank’s liq
... Show MoreThe basic objective of the research is to study the quality of the water flow service in the Directorate of Karbala sewage and how to improve it after identifying the deviations of the processes and the final product and then providing the possible solutions in addressing the causes of the deviations and the associated quality gaps. A number of quality tools were used and applied to all data Stations with areas and activities related to the drainage of rainwater, as the research community determines the stations of lifting rainwater in the Directorate of the streams of Karbala holy, and the station was chosen Western station to apply the non-random sampling method intended after meeting a number of. It is one of the largest and m
... Show Moreبهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته
... Show MoreIn this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s
... Show MoreResearch Summary:
Seeking happiness and searching for it have been among the priorities of mankind from the beginning of his creation and will remain so until the end of this world, and even in the next life, he seeks happiness, but the difference is that a person can work in this world to obtain it, but in the next life he is expected to get what he done in this world. And among these reasons are practical actions that a person undertakes while he intends to draw close to God Almighty, so they lead him to attain his desired perfection, and to attain his goals and objectives, which is the minimum happiness in this life, and ultimate happiness after the soul separates the body, and on the day of the judgment, Amon
... Show MoreIn high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri
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