The basic analytical formula for particle-hole state densities is derived based on the non-Equidistant Spacing Model (non-ESM) for the single-particle level density (s.p.l.d.) dependence on particle excitation energy u. Two methods are illustrated in this work, the first depends on Taylor series expansion of the s.p.l.d. about u, while the second uses direct analytical derivation of the state density formula. This treatment is applied for a system composing from one kind of fermions and for uncorrected physical system. The important corrections due to Pauli blocking was added to the present formula. Analytical comparisons with the standard formulae for ESM are made and it is shown that the solution reduces to earlier formulae providing more general way to calculate state density. Numerical calculations then are made and the results show that state density behavior with excitation energy deviates from Ericson’s and Williams’ formulae types, especially at higher excitation energies
The blade pitch angle (BPA) controller is key factor to improve the power generation of wind turbine (WT). Due to the aerodynamic structural behavior of the rotor blades, wind turbine system performance is influenced by pitch angle and environmental conditions such as wind speed, which fluctuate throughout the day. Therefore, to overcome the pitch angle control (PAC) problem, high wind speed conditions, and due to type-1 and type-2 fuzzy logic limitations for handling high levels of uncertainty, the newly proposed optimal hybrid type-3 fuzzy logic controller has been applied and compared since type-3 fuzzy controllers utilize three-dimensional membership functions, unlike type-2 and type-1 fuzzy logic controllers. In this paper six differen
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
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In the current research, multiple mixing ratios of gamma -transitions of the energy levels 60𝑁𝑑 142−150 isotopes populated in 𝑁𝑑(𝑛, 𝑛 ˊ 60 142−150 ) 60𝑁𝑑 142−150 interaction are calculated using the constant statistical tensor (CST) method. The results obtained are, in general, in good agreement or consistent, within the experimental error, with the results published in the previously researches. Existing discrepancies result from inaccuracies in the experimental results of previous works. The current results confirm the validity of the constant statistical tenser method of calculating the values of mixing ratios and its predictability of errors in experimental results
Semi-empirical methods were applied for calculating the vibration frequencies and IR absorption intensities for normal coordinates of the {mono (C56H28), di (C84H28), tri (C112H28) and tetra (C140H28)} -rings layer for (7,7) armchair single wall carbon nanotube at their equilibrium geometries which were all found to have D7d symmetry point group.
Assignment of the modes of vibration (3N-6) was done depending on the pictures of their modes by applying (Gaussian 03) program. Comparison of the vibration frequencies of (mono, di, tri and tetra) rings layer which are active in IR, and inactive in Ramman spectra. For C-H stretching vibrat
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Background: Schneiderian first rank symptoms are
considered highly valuable in the diagnosis of
schneideria.
They are more evident in the acute phase of the
disorder and fading gradually with time. Many studies
have shown that the rate of these symptoms are
variable in different countries and are colored by
cultural beliefs and values.
Objectives: To find out the rate of Schneiderian first
rank symptoms among newly diagnosed schizophrenic
patients, to assess which symptom(s) might
predominate in those patients, and to find out if there
is/are any correlation(s) between the occurrence of
these symptoms and the sex of the patients.
Methods: Out of twenty-four patients with no past
psychiatric hi
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