n this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the types of the kernel boundary func

An efficient modification and a novel technique combining the homotopy concept with  Adomian decomposition method (ADM) to obtain an accurate analytical solution for Riccati matrix delay differential equation (RMDDE) is introduced  in this paper  . Both methods are very efficient and effective. The whole integral part of ADM is used instead of the integral part of homotopy technique. The major feature in current technique gives us a large convergence region of iterative approximate solutions .The results acquired by this technique give better approximations for a larger region as well as previously. Finally, the results conducted via suggesting an efficient and easy technique, and may be addressed to other non-linear problems.

The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

: The need for means of transmitting data in a confidential and secure manner has become one of the most important subjects in the world of communications. Therefore, the search began for what would achieve not only the confidentiality of information sent through means of communication, but also high speed of transmission and minimal energy consumption, Thus, the encryption technology using DNA was developed which fulfills all these requirements [1]. The system proposes to achieve high protection of data sent over the Internet by applying the following objectives: 1. The message is encrypted using one of the DNA methods with a key generated by the Diffie-Hellman Ephemeral algorithm, part of this key is secret and this makes the pro

In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g