In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

Foreign direct investment (FDI) is one of the most practical types of foreign investment. FDI contributes to job creation, foreign exchange earnings and national income escalation, improving semi-skill and skilled labor. Based on our knowledge, this paper is the first study attempting to investigate the effect of political stability on the FDI in Turkey using an econometric approach. Achieving this objective, a co-integration analysis was conducted between the FDI and its determinants in the short-run and long-run including “macroeconomic indicators” and “Political Stability (PS)” in Turkey. Using annual data from 1974 to 2017 via Auto-Regressive Distributed Lag (ARDL) model. The results confirm the positive correlation betwe

       This study introduces a series of single and pile group model tests subjected to lateral loads in . multilayered sand from Karbala, Iraq. The aim of this study is to investigate: the performance of the pile groups subjected to lateral loads; in which the pile batter inclination angle is changed; the effect of pile spacing (s/d) ratio, the influence of using different number of piles and pile group configuration. Results revealed that the performance of single negative (Reverse) Battered piles with inclination of 10° and 20° show a gain of 32% and 76 % in the ultimate lateral capacity over the regular ones. For pile groups, the use of a combination of regular, negative and positive battered piles in

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

The aim of the present research is to investigate the effecting of pH parameter on the feasibility of lead removal from simulated wastewater using an electrochemical system. Electrocoagulation method is one of electrochemical technology which is used widely to treat industrial wastewater. Parameters affecting this operation, such as initial metal concentration, applied current, stirrer speed, and contact time of electroprocessing were taken as 155ppm, 1.5 Ampere, 150 rpm, 60 minutes respectively. While pH of the simulated wastewater was in the range of  2 to 12 in the experiments. It was found from the results that pH is an important parameter affecting lead removal operation. The best value of pH parameter is appro

The increased size of grayscale images or upscale plays a central role in various fields such as medicine, satellite imagery, and photography. This paper presents a technique for improving upscaling gray images using a new mixing wavelet generation by tensor product. The proposed technique employs a multi-resolution analysis provided by a new mixing wavelet transform algorithm to decompose the input image into different frequency components. After processing, the low-resolution input image is effectively transformed into a higher-resolution representation by adding a zeroes matrix. Discrete wavelets transform (Daubechies wavelet Haar) as a 2D matrix is used but is mixed using tensor product with another wavelet matrix’s size. MATLAB R2021