Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

Cloud computing offers a new way of service provision by rearranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in the cloud. Traditional deduplication schemes cannot work on encrypted data. Among these data, digital videos are fairly huge in terms of storage cost and size; and techniques that can help the legal aspects of video owner such as copyright protection and reducing the cloud storage cost and size are always desired. This paper focuses on v

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

QA Sarhan, University of Anbar Sport and Physical Education Sciences, 2019

This research sheds light on one of the important and vital topics for the banking sectors (technical requirements for the application of economic intelligence) namely by (Hardware, equipment, communication networks, software, databases). And the dimensions of the strategic success of the banks represented by(Customer satisfaction, customer trust, quality of service, growth) In the three Iraqi private banks, namely(Assyria International Investment, Mansour Investment, International Development Investment and Finance). Its implementation is an urgent necessity in order to improve the quality of its banking services to win the satisfaction of its customers and their confidence and then grow to achieve stra

The last ten years observed a shift enormous scientific in the method and way that it deals professional with the cost accounting and reflected the result those shift enormous scientific of increase the competitive environmental that accompanied the emergence of a modern manufacturing environmental on surface the long roductive life and emergence advanced information technology that give a central focus of his important on client with growing global markets growth on a large scale.

        The research aim to define the concept of cost awareness, the concept and methods of  strategic cost management and the role of cost awareness for managers of industrial units in strategic of cost managem

Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately de