This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compared to traditional regression models: These estimates are robust to outliers and heterogeneous spatial effects and capture fully conditional distributions with respect to mean regression models. The review supports future work toward enhancing estimation approaches and possible SARQR application extensions to other fields. The spatial modeling has applicability in the research, decision-making, and profession formulation because it encourages a broader SARQR application in economic analysis, infrastructure planning, and public health policy. Future research must aim at refining estimation methods and integrating SARQR with other models of analysis to optimize its usefulness in utilizing sophisticated spatial data.
Industrial Investment according to Clean Productive methods is an important element in the process of rational use of Economic Resources, and the Iraqi industrial sector relied on traditional production methods; the productive activities in this sector did not take into consideration the environmental dimension, which leads to achieving the optimal use of economic resources, so it was necessary to have new investment trends heading with Clean Production. Therefore, the research is based on the hypothesis that "Clean Production contributes to improving the environment and rational use of Natural Resources." Based on the descriptive - inductive analysis methodology that study of Iraqi industries with Clean Production,
... Show MoreIn this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.
This world is moving towards knowledge economy which basically depends on knowledge and information. So, the economic units need to develop its financial reporting system which helps to provide useful information in timeliness for investors in accordance with the requirements of the knowledge economy and meets the needs of those investors. This research aims to revealing the reflects of knowledge economy on the approaches of financial reporting and suggesting a financial reporting model in the environment of knowledge economy, depending on combining the value approach with the events approach using database and communication technology and providing useful accounting information for all users regardless of
... Show MoreIn this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
... Show MoreFree radical formation in heme proteins is recognized as a factor in mediating the toxicity of many chemicals. The present study was designed to evaluate the dose-response relationship of the free radical scavenging properties of pentoxifylline in nitrite-induced Hb oxidation. Different concentrations of pentoxifylline were added at different time intervals of Hb oxidation in erythrocytes lysate, and formation of methemoglobin (MetHb) was monitored spectrophotometrically. The results showed that in this model, pentoxifylline successfully attenuates Hb oxidation after challenge with sodium nitrite; this protective effect was found to be not related to the catalytic stage of Hb oxidation, th
... Show MoreIn this paper, a Sokol-Howell prey-predator model involving strong Allee effect is proposed and analyzed. The existence, uniqueness, and boundedness are studied. All the five possible equilibria have been are obtained and their local stability conditions are established. Using Sotomayor's theorem, the conditions of local saddle-node and transcritical and pitchfork bifurcation are derived and drawn. Numerical simulations are performed to clarify the analytical results