The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through  finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy

The effective application of the method of measuring and evaluating performance according to the Balanced  Scorecard the need for an information system a comprehensive and integrated for internal and external environment, Which requires the need to develop accounting information system in general and cost management information systems to suit the particular requirements of the environment in terms of the development of modern methods of measurement to include the use of some methods that have proven effective in measuring and evaluating performance.

The research problem in need of management to develop methods of measuring and evaluating performance through the use of both financial measures and non

The paper uses the Direct Synthesis (DS) method for tuning the Proportional Integral Derivative (PID) controller for controlling the DC servo motor. Two algorithms are presented for enhancing the performance of the suggested PID controller. These algorithms are Back-Propagation Neural Network and Particle Swarm Optimization (PSO). The performance and characteristics of DC servo motor are explained. The simulation results that obtained by using Matlab program show that the steady state error is eliminated with shorter adjusted time when using these algorithms with PID controller. A comparative between the two algorithms are described in this paper to show their effectiveness, which is found that the PSO algorithm gives be

Background: Psoriasis is an immune-mediated inflammatory disease with unknown aetiology that may be associated with the defect in proliferation and differentiation of the keratinocytes related to inflammatory cell infiltration. According to published reports, it is universal in occurrence; its prevalence in different populations varies from 0.1% to 11.8%. Receiving Apremilast resulted in a strong reduction in interleukin 17 and interleukin 23, as well as reduced expression of other inflammatory cytokines and improvement of psoriatic lesions. Objectives: This study aimed to assess the impact of Apremilast on levels of IL-17, IL-23, and lipids in obese psoriatic patients. Methods: Thirty obese patients with psoriasis were included in

Background: The appointment system is a common practice in primary health care clinics in developed countries. The patients and health care providers in the primary health care setting perceived the appointment system as an indicator of good quality service.

Objective: The aim of this study was to survey patients’ and health care providers’ attitudes towards the introduction of an appointment system and their satisfaction with the existing ‘walk-in’ system in the primary health care setting.

Subjects and Methods: A questionnaire survey was conducted included a convenient sample of 234 patients as well as 76 health care providers from two primary health care center

<span lang="EN-US">In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, and industry. In this paper, the physical prototype of a proposed self-balancing platform that described the self-balancing attitude in the (X-axis, Y-axis, or biaxial) under the influence of road disturbance has been introduced. In the physical prototype, the inertial measurement unit (IMU) sensor will sense the disturbance in (X-axis, Y-axis, and biaxial). With the determined error, the corresponding electronic circuit, DC servo motors, and the Arduino software, the platform overcame the tilt angle(disturbance). Optimization of the proportional-integral-

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.