The binary cluster model (BCM) and the two-frequency shell model (TFSM) have been used to study the ground state matter densities of neutron-rich 6He and 11Li halo nuclei. Calculations show that both models provide a good description on the matter density distribution of above nuclei. The root-mean square (rms) proton, neutron and matter radii of these halo nuclei obtained by TFSM have been successfully obtained. The elastic charge form factors for these halo nuclei are studied through combining the charge density distribution obtained by TFSM with the plane wave Born approximation (PWBA).
ABSTRACT
In this research been to use some of the semi-parametric methods the based on the different function penalty as well as the methods proposed by the researcher because these methods work to estimate and variable selection of significant at once for single index model including (SCAD-NPLS method , the first proposal SCAD-MAVE method , the second proposal ALASSO-MAVE method ) .As it has been using a method simulation time to compare between the semi-parametric estimation method studied , and various simulation experiments to identify the best method based on the comparison criteria (mean squares error(MSE) and average mean squares error (AMSE)).
And the use
... Show MoreThe main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate
... Show MoreThis paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul
... Show MoreIn this work, the technique of attenuation of gamma ray to calculate the density of comet nucleus materials (C/2009 P1 (GARRADD) at different range of energy (0.2- 0.9 MeV). also, the single scattering model for gamma rays has been assumed that photons reaching the detector with scattered only once in the material. The program has been designed and written in FORTRAN language (77 – 90) to calculate the density for molecules using Monte Carlo method was used to simulate the scattering and absorption of photons in semi- infinite material. Gamma ray interacts with the matter by three mainly interactions: Photoelectric effect, Compton scattering and Pair production (electron and positron). On the 137Cs source energy (662 keV), Compton scat
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe main problem of the current study concentrates on applying critical discourse analysis to examine textual, discoursal and social features of reduplication in some selected English newspaper headlines. The main aim of the current study is to analyze the linguistic features of reduplication by adopting Fairclough's three-dimensional model (2001). This study sets forth the following hypotheses: (1) English headline – newspapers comprise various textual, discoursal and social features ;(2)the model of analysis is best suited for the current study.To achieve the aims and verify the hypotheses, a critical discourse analysis approach is used represented by Fairclough's socio-cultural approach (2001).The present study has examined the use of
... Show MoreInformation security contributes directly to increase the level of trust between the government’s departments by providing an assurance of confidentiality, integrity, and availability of sensitive governmental information. Many threats that are caused mainly by malicious acts can shutdown the egovernment services. Therefore the governments are urged to implement security in e-government projects.
Some modifications were proposed to the security assessment multi-layer model (Sabri model) to be more comprehensive model and more convenient for the Iraqi government. The proposed model can be used as a tool to assess the level of security readiness of government departments, a checklist for the required security measures and as a commo
This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time
... Show MoreMultilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d
Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based
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