This research seeks through the adoption of two basic variables, where he considered the actuarial experience as an independent variable, while the process of accepting the risk and dimensions related to it is a dependent variable, the research was adopted to present the data achieved by the company during the life insurance business during the adoption of actuarial experience at the beginning of its work where Adoption of the historical method in the analysis of those data to prove the researcher's opinion, through the analysis of data (5 years) for the first period, which extends between (1975-1979), the period during which the company adopted the actuarial experience at the time, also taken data for the same dimensions related to the

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين  في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من  السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ

Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient

This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Dam operation and management have become more complex recently because of the need for considering hydraulic structure sustainability and environmental protect on. An Earthfill dam that includes a powerhouse system is considered as a significant multipurpose hydraulic structure. Understanding the effects of running hydropower plant turbines on the dam body is one of the major safety concerns for earthfill dams. In this research, dynamic analysis of earthfill dam, integrated with a hydropower plant system containing six vertical Kaplan turbines (i.e., Haditha dam), is investigated. In the first stage of the study, ANSYS-CFX was used to represent one vertical Kaplan turbine unit by designing a three-dimensional (3-D) finite element (F

This study is about finding the estimation of tow equations, the comparative has been done between the estimations  by using seemingly unrelated regression equations for the variable and random error has been distribution with poisson and the variable and random error has been distribution with normal and the method by using oldenary lest square.

While in the application side, we have estimated the parameter of investment specification function for the sector of agriculture with the industry sector is enabled us to obtain an estimation efficiency for the model of seemingly unrelated Poisson regression equation.

المستخلص