The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Quadrupole Q moments and effective charges are calculated for ⁹C, ¹¹C, ¹⁷C and ¹⁹C exotic nuclei using shell model calculations. Excitations out of major shell space are taken into account through a microscopic theory which are called core-polarization effects. The simple harmonic oscillator potential is used to generate the single particle matrix elements of ^9,11,17,19C. The present calculations with core-polarization effects reproduced the experimental and theoretical data very well.

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

الغرض - تعتمد هذه الدراسة على المنهج الوصفي التحليلي من خلال جمع البيانات اللازمة وتحليلها، كون هذا المنهج يركز على استطلاع الآراء لعينة البحث وتوجهاتها ، وتهدف إلى تطوير نموذج يدرس العلاقة بين خلق المعرفة والبراعة التنظيمية في المصارف الخاصة العراقية والتحقق من صحته تجريبياً. التصميم / المنهجية / المدخل- تم إجراء مسح عبر استمارة استبيان لجمع البيانات من عينة من (113) مدير من مصارف تجارية خاصة بالإضافة إلى ذلك ا

The performance of flexible pavements is significantly impacted by the permanent deformation (rutting) of asphalt pavements. Rutting shortens the pavement's useful service life and poses significant risks to those using the highway since it alters vehicle handling characteristics.. The aim of this research is to evaluate the permanent deformation of asphalt mixtures under different conditions,to achieve this aim 108 cylindrical specimens has been prepared and tested under repeated loading in uniaxial compression mode. Five factors were considered in this research, these factors represent the effect of environmental condition and traffic loading as well as mixture properties, they include testing temperature, loading condition (stress level

  Weibull distribution is considered as one of the most widely  distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.

   In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th