The relationship between the GDP, FDI, and non-oil exports in the Saudi economy - 1970-2019: Evidence from (VECM) and (ARDL) assessment - according to Vision 2030

Abstract. This study examines the long-term and short-term balance relationship of GDP, Foreign Direct Investment to the performance of nonoil exports in KSA within the framework of the export-led growth (ELG) hypothesis: Evidence from ARDL, VECM and a smaller evaluation according to Vision 2030. We performed an analysis for the period from 1970 to 2019 by an autoregressive distributed lag (ARDL) model and checked the robustness of the results in the vector error correction (VECM) model. The co-integration and Toda - Yamamoto causality analysis are conducted by using two techniques of vector error correction model (VECM) and autoregressive distributed lag (ARDL). The main findings are: Foreign direct investment can increase GDP growth rates by increasing non-oil exports in the Saudi economy according to the results of the Toda - Yamamoto Causality Test; and the GDP in the Saudi economy are affected by FDI and the rates of non-oil exports, in the long and short term, and the reason is the strength of the reserves of the Saudi economy. The contribution of this research is that the outcomes found by means of econometric models can be used for predicting and measuring GDP in upcoming years, can get a guideline from this research To the economic policy makers in Saudi Arabia. Also, the dynamic interaction among FDI, non-oil exports, and economic growth is investigated using the ARDL. The ARDL co-integration results showed that GDP, FDI and non-oil exports are co-integrated, indicating the presence of a long-run equilibrium relationship between them. Besides, the results for the relationship between GDP, FDI and Non-Oil Exports are interesting and indicate that there is no significant from variables and vice-versa using Toda-Yamamoto causality.Keywords. GDP, FDI, Non-oil exports, Stationary, Toda-Yamamoto Test, VECM, ARDL.JEL. D42, D43, H21, L12, L13

Evolution of Patient Dose in Chest Radiotherapy Planning

Radiographic image has been used for patient positioning, target localization radiation beam alignment, and subsequent verification of treatment delivery in radiotherapy. Radiographic imaging as all medical use of ionizing radiation can give significant exposure to the patient. The aim of this study was to determine the radiological dose for chest imaging. Imaging dose during course of radiotherapy add dose to high therapeutic dose therefore this raises the issue of the balance between the benefit of these additional imaging exposures and the associated risk of radiation induced cancer arising from them. Therefore, estimation of imaging doses and possibility of its risk is necessary to provide adequate justification of this exposure. In this dissertation the main investigated type of the X-ray simulation were chest AP and PA, the total number of patients was 10 ( 62 radiographs). The fluctuation of the entrance surface dose (ESD) was relatively ranging from 0.35 micro;Gy to 8.43 micro;Gy for AP projection, and from 0.12 micro;Gy to 0.46 micro;Gy for PA projection. The mean values of ESD were found to be within guidance limits which was proposed in some countries (CEC 2004, and Germany 2003)

Quantum Heat Flow Model for Heat Flow in Some Nanotubes

Using Schrodinger equation in a fractional medium a useful expression for heat flow through Nano tubes has been found. Fortunately, this equation resembles  that obtained by Moran Wang etal, and Hai- Dong Wang teal.   the ordinary thermal conductivity is constant. The effective thermal conductivity temperature dependent resembles that obtained for carbon Nano tubes and Boron Nitride Nano tubes. It is also finite at low temperature which also conforms with experimental data for carbon and Boron. Since Nano materials are described by quantum lows, this new model is thus more suitable for Nano tubes, as for as it is derived using quantum laws

Electric Circuit Recognition

A computer vision technique is developed to analyze an AC circuit's drawing and produce a circuit description program suitable for analysis such as SPICE. The algorithm proposed uses a variety of machine vision techniques to locate the circuit nodes and isolate the circuit components. Moments scale invariant descriptors are then used to recognize both the elements and values

Electric Circuit Recognition

A computer vision technique is developed to analyze an AC circuit's drawing and produce a circuit description program suitable for analysis such as SPICE. The algorithm proposed uses a variety of machine vision techniques to locate the circuit nodes and isolate the circuit components. Moments scale invariant descriptors are then used to recognize both the elements and values