The relative strength index (RSI) is one of the best known technical analysis indicators; it provides the speculators by prior signals about the future stock’s prices, and because the speculations in shares of companies which listed in the Iraq Stock Exchange have a high degree of risk, like risk of shares prices felling, so the speculators became committed to use some methods to reduce these risks, and one of these methods is the technical analysis by using the relative strength index (RSI) which enable the speculators of choosing the right time for buy and sell the stocks and the right time to enter or leave the market by using the historical rice data. And from here the problem of the research formulated as “Is the using of

In this study, the effects of blending the un-branched acrylate polymer known as Poly (n-decyl acrylate), and the branched acrylate polymer known as Poly (iso-octyl acrylate), on the viscosity index (VI), and the pour point of the Iraqi base stocks 40, and 60 respectively, were investigated. Toluene was used as a carrier solvent for both polymer types. The improvement level of oils (VI, & pour point) gained by blending the oil with the acrylate derived polymers was compared with the values of (VI, and pour point) gained by blending the oil with a commercial viscosity index, and pour point improver. The commercial lubricant additive was purchased and used by Al-Daura Refineries. It consisted of an un-known olefin copolymer dissolved i

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Introduction: Ostrich farming has emerged as a new livestock industry in Iraq, but scientists lack sufficient information on health concerns, including intestinal parasites that cause significant production losses and financial instability over extended periods. Methods: Researchers collected 150 fecal samples from ostriches that dwelled in central and southern Iraq for microscopic examination of intestinal parasite occurrence. Results: The six parasite species included Entamoeba sp., which made up 26.66% of the population, and Cryptosporidium sp. at 11.33%, Ascaridia galli at 10%, Giardia sp. at 4.6%, Raillietina sp. at 2%, and Trichostrongyl. Molecular analysis was performed on a subset of positive samples because Entamoeba sp. is

The aim of this study is modeling the transport of industrial wastewater in sandy soil by using finite element method. A washing technique was used to remove the industrial wastewater from the soil. The washing technique applied with an efficient hydraulic gradient to help in transport of contaminant mass by advection. Also, the mass transport equation used in modeling the transport of industrial wastewater from soil includes the sorption and chemical reactions. The sandy soil samples obtained from Al-Najaf Governorate/Iraq. The wastewater contaminant was obtained from Al- Musyiebelectricity power plant. The soil samples were synthetically contaminated with four percentages of 10, 20, 30 and 40% of the contaminant and these percentages calc