Electric Quadrupole transitions are calculated for beryllium isotopes (9, 10, 12 and 14). Calculations with configuration mixing shell model usually under estimate the measured E2 transition strength. Although the consideration of a large basis no core shell model with 2ℏtruncations for 9,10,12 and14 where all major shells s, p, sd are used, fail to describe the measured reduced transition strength without normalizing the matrix elements with effective charges to compensate for the discarded space. Instead of using constant effective charges, excitations out of major shell space are taken into account through a microscopic theory which allows particle–hole excitations from the core and model space orbits to all higher orbits

Fiber Bragg Grating has many advantages where it can be used as a temperature sensor, pressure sensor or even as a refractive index sensor. Designing each of this fiber Bragg grating sensors should include some requirements. Fiber Bragg grating refractive index sensor is a very important application. In order to increase the sensing ability of fiber Bragg gratings, many methods were followed. In our proposed work, the fiber Bragg grating was written in a D-shaped optical fiber by using a phase mask method with KrFexcimer. The resultant fiber Bragg grating has a high reflectivity 99.99% with a Bragg wavelength of 1551.2 nm as a best result obtained from a phase mask with a grating period of 1057 nm. In this work it was found that the rota

Design sampling plan was and still one of most importance subjects because it give lowest cost  comparing with others, time live statistical distribution should be known to give best estimators for  parameters of sampling plan and get best sampling plan.

Research dell with design sampling plan when live time distribution follow Logistic distribution with () as location and shape parameters, using these information can help us getting (number of groups, sample size) associated with reject or accept the Lot

Experimental results for simulated data shows the least number of groups and sample size needs to reject or accept the Lot with certain probability of

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In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

Multilateral wells require a sophisticated type of well model to be applied in reservoir simulators to represent them. The model must be able to determine the flow rate of each fluid and the pressure throughout the well. The production rate calculations are very important because they give an indication about some main issues associated with multi-lateral wells such as one branch may produce water or gas before others, no production rate from one branch, and selecting the best location of a new branch for development process easily.                                &nbsp

In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete