Preferred Language
Articles
/
Gxip8JUBVTCNdQwC44Ao
Spatial Quantile Autoregressive Model: A Review
...Show More Authors

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.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Mar 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Improved optimality checkpoint for decision making by using the sub-triangular form
...Show More Authors

Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

... Show More
View Publication Preview PDF
Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
Direct method for Solving Nonlinear Variational Problems by Using Hermite Wavelets
...Show More Authors

In this work, we first construct Hermite wavelets on the interval [0,1) with it’s product, Operational matrix of integration 2^k M×2^k M is derived, and used it for solving nonlinear Variational problems with reduced it to a system of algebric equations and aid of direct method. Finally, some examples are given to illustrate the efficiency and performance of presented method.

View Publication Preview PDF
Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Analyzing big data sets by using different panelized regression methods with application: Surveys of multidimensional poverty in Iraq
...Show More Authors

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

... Show More
View Publication
Scopus
Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
Assessing of Some Toxic Heavy Metals Levels and Using Geo Accumulation Index in Sediment of Shatt Al-Arab and the Iraqi Marine Region
...Show More Authors

Mercury, arsenic, cadmium and lead, were measured in sediment samples of river and marine environmental of Basra governorate in southern of Iraq. Sixteen sites of sediment were selected and distributed along Shatt Al-Arab River and the Iraqi marine environment. The samples were distributed among one station on Euphrates River before its confluence with Tigris River and Shatt Al-Arab formation, seven stations along Shatt Al-Arab River and eight stations were selected from the Iraqi marine region. All samples were collected from surface sediment in low tide time. ICP technique was used for the determination of mercury and arsenic for all samples, while cadmium and lead were measured for the same samples by using Atomic Absorption Spectrosc

... Show More
View Publication Preview PDF
Scopus (10)
Scopus Clarivate Crossref
Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Magic square
...Show More Authors

In this paper we introduce two Algorithms, the first Algorithms when it is odd order and how we calculate magic square and rotation for it. The second Algorithms when it be even order and how to find magic square and rotation for it.

View Publication Preview PDF
Crossref
Publication Date
Wed Jul 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Fast and robust approach for data security in communication channel using pascal matrix
...Show More Authors

This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

... Show More
View Publication
Scopus (7)
Crossref (2)
Scopus Crossref
Publication Date
Fri Jan 15 2021
Journal Name
Obstetrics & Gynecology Science
Effects of excessive tea consumption on pregnancy weight gain and neonatal birth weight
...Show More Authors

Objective Tea lovers are increasing worldwide. We hope that this report is the first to discuss the possible impacts of high black tea consumption on gestational weight gain (GWG) and birth parameters. Methods Throughout one year, a total of 7,063 pregnant ladies coming for first antenatal visit were screened in a major tertiary center. Of them, 1,138 were involved and divided according to their preference into 3 groups: excessive tea (ET), usual tea (UT), and mixed beverages group. The study included women who gave birth to healthy neonates. Results The rate of ET consumption was 4.13% with a total of 41 cases. The UT group (controls) comprised 94 women. ET was significantly associated (P<0.05) with maternal age, parity, occupation, smokin

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Thu Feb 15 2024
Journal Name
Journal Of Al-turath University College
A Comparison of Traditional and Optimized Multiple Grey Regression Models with Water Data Application
...Show More Authors

Grey system theory is a multidisciplinary scientific approach, which deals with systems that have partially unknown information (small sample and uncertain information). Grey modeling as an important component of such theory gives successful results with limited amount of data. Grey Models are divided into two types; univariate and multivariate grey models. The univariate grey model with one order derivative equation GM (1,1) is the base stone of the theory, it is considered the time series prediction model but it doesn’t take the relative factors in account. The traditional multivariate grey models GM(1,M) takes those factor in account but it has a complex structure and some defects in " modeling mechanism", "parameter estimation "and "m

... Show More
View Publication
Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
...Show More Authors

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

... Show More
View Publication Preview PDF
Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
Estimation of urban land price within holly cities by using integrated GIS-regression models: case study Al-Kufa city- Iraq
...Show More Authors

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

... Show More
View Publication Preview PDF