This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ₁and  λ₂  , also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i

In this research was to use the method of classic dynamic programming (CDP) and the method of fuzzy dynamic programming (FDP) to controlling the inventory in N periods and only one substance ,in order to minimize the total cost and determining the required quantity in warehouse rusafa principal of the ministry of commerce . A comparison was made between the two techniques، We found that the value of fuzzy total cost is less than that the value of classic total cost

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

The most important contemporary issues which related to the survey of the influence of communication development technology to land use sustainability. The research aims to explain the changes that happened in the quality & land use activities performance by understanding the transformations due to modern technology and its impact on current uses and its impact on changing functional relationships between those uses to create new combinations or hybrid uses.Research will follow the analytical descriptive approach in presenting the problem of research. Research has several conclusions & recommendations, one of conclusions is the change of the place concept and its relation to changing the concept of land use and its sustai

Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan

It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases :  first, in real data; and secondly,  after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for  comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.

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

One of the critical factors for dental implant success is accurate clinical and radiological assessment. Cone-beam computed tomography systems (CBCT) allow surgeons to determine the quality and quantity before surgery, aiding in treatment planning. This study highlights the importance of such an assessment Materials and Methods A total of 40 patients were referred to CBCT scanning for pre-dental implant assessment in the Oral and Maxillofacial Radiology department at Al-Shaheed Gazi Al Hariri Hospital from 2021 to 2022. The patients were between 18 and 50 years old. All data were analyzed with on-demand 3D software (Kavo OP 3D: Cone Beam 3D imaging Germany). Results: Regarding the ridge shape: In the upper anterior and posterior regions, th